curriculum (scheme of examination) & syllabus · engineering. 2. to make b.tech-computer...

Curriculum (Scheme of Examination) &

Syllabus

for

B.Tech-Computer Science & Engineering

Batch 2016-17 onwards

SGT University Gurgaon Credit Based Scheme w.e.f. 2016-2017


I SEMESTER

S.No

Course title

Schedule

L T P C

1 Basic English 0 0 4 2

2 Engineering Physics 3 0 0 3

3 General Chemistry (CSE&CE) / Environmental Science (ME&ECE) 3 0 0 3

4 Advanced Calculus & Matrices 3 1 0 4

5 Basic Engineering – I (CSE&CE) / Basic Engineering – II (ME&ECE) 2 0 0 2

6

Computer Programming and Problem Solving (CSE&CE) / Basic Electrical & Electronics Engineering (ME&ECE)

3

0

0

3

7 Workshop Technology (CSE&CE) / Engineering Drawing (ME&ECE) 0 0 2/ 1/2

8 Engineering Physics Lab 0 0 2 1

9 General Chemistry Lab (CSE&CE) 0 0 2 1

10

Computer Programming and Problem Solving Lab (CSE&CE) / Basic Electrical & Electronics Engineering Lab (ME&ECE)

0

0

2

1

TOTAL 14 1 10/11 21/22


II SEMESTER

S.No

Course title

Schedule

L T P C

1 English Proficiency 0 0 4 2

2 Advanced Material Physics 3 0 0 3

3 General Chemistry (ME&ECE) / Environmental Science (CSE&CE) 3 0 0 3

4 Differential Equation Laplace Transform 3 1 0 4

5 Basic Engineering – I (ME&ECE) / Basic Engineering – II (CSE&CE) 2 0 0 2

6

Computer Programming and Problem Solving (ME&ECE) / Basic Electrical & Electronics Engineering (CSE&CE)

3

0

0

3

7 Workshop Technology (ME&ECE) / Engineering Drawing (CSE&CE) 0 0 2/ 1/2

8 Advanced Material Physics Lab 0 0 2 1

9 General Chemistry Lab (ME&ECE) 0 0 2 1

10

Computer Programming and Problem Solving Lab (ME&ECE) / Basic Electrical & Electronics Engineering Lab (CSE&CE)

0

0

2

1

TOTAL 14 1 10/11 21/22


III SEMESTER

S.no

Course title Teaching Schedule

L T P C

1 Technical Skills for Computer Engineers-I 0 0 2 1

2 Professional communication (Soft skills –III) 0 0 4 2

3 Universal Human values 2 0 0 2

4 Foreign Language (German/French) - I 2 0 2 3

5 Data Structure and Algorithms using C 3 0 0 3

6 Computer Architecture & Organization 3 0 0 3

7 Discrete Mathematics 3 1 0 4

8 Digital Electronics 3 0 0 3

9 Data Structure & Algorithms Lab 0 0 2 1

10 Digital Electronic Lab 0 0 2 1

11 Industrial Exposure-I - - - 1

Total 16 1 12 24


IV SEMESTER

S.no

Course title

Teaching Schedule

L T P C

1 Aptitude Building

0

0

4

2

2

Technical Skills for CSE-II (Linux)

0

0

2

1

3

Foreign Language (German/French) - II

2

0

2

3

4

Physiology & Sociology

2

0

0

2

5

Numerical Methods and Random Process

3

1

0

4

6

Object Oriented Programming Using C++

3

0

0

3

7

Database Management System

3

0

0

3

8

Operating System

3

0

0

3

9

Computer Graphics

3

0

0

3

10

C++ Programming Lab

0

0

2

1

11

Database Management System Lab

0

0

2

1

12

Computer Graphics Lab

0

0

2

1

13

Industrial Training - I

-

-

-

2

Total

19

1

14

29


V SEMESTER

S.no

Course title

Teaching Schedule

L T P C 1 Personality & Career Building 0 0 4 2

2 Technical skills for CSE-III 0 0 2 1

3 Entrepreneurship Development 2 0 0 2

4 Computer Networks 3 0 0 3

5 (Department Elective –I) 3 0 0 3

6 Analysis and Design of Algorithms 3 0 0 3

7 (Faculty Elective I/II/III) 3 0 0 3

8 Compiler Design 3 0 0 3

9 Software Engineering 3 0 0 3

10 Computer Networks Lab 0 0 2 1

11 Software Engineering Lab 0 0 2 1

12 Industry Exposure-II - - - 1 Total 20 0 10 26

*Department Elective-I

E-Commerce Soft Computing Data Compression


VI SEMESTER

S.no

Course title

Teaching Schedule

L T P C 1 Campus to Corporate 0 0 4 2

2 Technical Skills for CSE-IV 0 0 2 1

3 Industrial Economy and Management 2 0 0 2

4 Probability & Statistics 3 0 0 3

5 Department Elective -II 3 0 0 3

6 Theory of Automata & Formal Language 3 0 0

3

7 Software Development &Testing Methodology

3 0 0 3

8 Advanced Java 3 0 0 3


10 Advance Java Programming Lab 0 0 2 1

11 Industrial Training - II - - - 2

Total 20 1 8 27

*Department Elective-II

Distributed System Wireless and Mobile Communication Enterprise Resource Planning


VII SEMESTER

S.no

Course title

Teaching Schedule

L T P C 1 Artificial Intelligence 3 0 0 3


3 Department Elective-III 3 0 0 3

4 Professional Ethics for Computer Engineers

2 0 0 2

5 Department Elective-IV 3 0 0 3

6 Open Elective 3 0 0 3

7 Industrial/Research Project (Phase-I)

0 0 2 5

8 Neural Networks Lab 0 0 2 1

14 0 4 20

* Department Elective -III

Software Project Management Image processing and Pattern Recognition Real Time System * Department Elective -IV Cloud Computing Bio informatics Neural Networks


VIII SEMESTER

S.no

Course title

Teaching Schedule

L T P/D 1 Business Intelligence 2 0 0 2

2 (Department Elective-V) 3 0 2 4 3 Industrial/Research Project (Phase-II) 0 0 2 15

Total 5 4 21

* Department Elective -V Android Apps Development Data Mining and Data Warehousing

Technical Skills for Computer Engineers-I Learning Schedule L T P C

Pre-requisites: Basic Knowledge of Computers 0 0 2 1

COURSE OBJECTIVES 1. To prepare students to build solid foundation in theory and practice of B.Tech-Computer Science &

Engineering. 2. To make B.Tech-Computer Science & Engineering graduates most competent, industry ready &

competitive in public and private organization 3. To build extensive foundation among students to take up higher study 4. To reduce the industry & academic gap & also train students as per current industry requirement.

COURSE OUTCOMES On completion of this course, the students will be able to:

1. Understand basic concepts of operating systems. 2. Compare various architectures based upon their features. 3. Use pointers and files in solving various programming problems 4. Apply Java data base connectivity 5. Use servlets in various applications 6. Understand the basic terminology used in computer programming 7. Write, compile and debug programs in C language. 8. Use different data types in a computer program. 9. Describe the process of problem solving. 10. Identify and employ techniques for generating possible solutions.

COURSE CONTENT Unit I: Computer Architecture & Microprocessor Computer organizations (Accumulator based/ General purpose register based/stack based), Addressing mode, RISC/CISC, Arithmetic circuits, basics of assembly language and microprocessors Unit II: Operating Systems Operating systems Basics: Process and threads, CPU scheduling, process synchronization, Memory management Unit III: C & Data structure Using files in C: Concepts of file pointers, opening files in read/write/append mode, reading data from file, appending/writing data, closing files, : Using Pointers: Concepts of pointers, declaring arrays and structures using pointers, Data Structure using pointers: Tree, list, red black tree using pointers Unit IV: Advanced Java JDBC: Types of drivers, Creating connections, executing query and making prepared statements, Servelets: Servlets life cycle, managing cookies, managing sessions and URL rewriting, handling form data. Unit V: Problem solving Solving logical problems related to these topics. Clearing students doubts, testing their level of understanding

TEXT BOOKS

1. Computer System Organization, Morris Mano, PHI 2. Operating system concepts, Silberschatz, Galvin, Willey 3. Understanding Pointers in C, Yashvant kanetkar, BPB Publications 4. Core Java vol. I & vol. II, C.S. Horstmann & G. Cornell, by sun micro systems 5. Java servlets & Java server pages, Marty Hall, Prentice Hall

REFERENCE BOOKS

1. Computer Organization, C. Hamacher, Mcgrew Hill. 2. Modern Operating System, Tanenbaum, Prentice Hall 3. The C programming Language, Kerningham & Ritchie, Prentice Hall

Professional Communication Learning Schedule L T P C

Pre-requisites: Basic knowledge of English 0 0 4 2

COURSE OBJECTIVE 1. Enhancing listening-speaking Skills 2. Enhance public speaking to further enhance the Grammar Skills 3. To understand skills pertaining to industry

COURSE OUTCOME: 1. To speak confidently before the audience 2. To be able to convey their ideas in an expressive and effective way 3.Get a holistic industry perspective

COURSE CONTENT

Unit-I: Writing Comprehension

Comprehension of Selected Passages from Stories and Articles, Grammatical Errors Detection, Errors in use of words, nouns, pronouns, adjectives etc i.e., all the grammatical categories, Error Detection, Errors in Sentence Formation: Tenses, Direct-Indirect Speech through Comprehension of Text from various Sources and Lab Software Unit-II: Reading Comprehension Developing Skills for Comprehension, Practice for Skills for Reading Comprehension, Using Text from Selected Stories/Newspapers and Handouts. Unit-III: Narration Finding out Topic Sentence, Order of Paragraph, Balance in Reading Comprehension, Emphasis will be Given on Correct Pronunciation and Intonation, Reading Practice and Exercise through Pictures, Video Clips and Software. Unit-IV: Reading Skills and Narration Reading Newspapers and Passages and Story Telling and Summarizing Unit-V: Career Building Mind Mapping, Career Planning, On camera exercises, Assessment Retake,

TEXT BOOKS

1. Sanjay Kumar and Pushp Lata „Communication Skills‟, Oxford University Press 2012. 2. Raymond Murphy „Essential English Grammar‟, Cambridge University Press 1998.

REFERENCE BOOKS

1. Meenakshi Raman and Sangeeta Sharma „Technical Communication Principles and Practice‟,

Oxford University Press 2012 2. Meenakshi Raman and Prakash Singh „Business Communication‟ Oxford University Press 2011

Universal Human Values Learning Schedule L T P C

Pre-requisites: Adaptive 2 0 0 2

COURSE DESCRIPTION: The methodology of this course is universally adaptable, involving a systematic and rational study of the human being vis-à-vis the rest of existence. It is free from any dogma or value prescriptions. This process of self-exploration takes the form of a dialogue between the teacher and the students to begin with and within the student himself/herself finally.

COURSE OBJECTIVE: 1. To create an awareness on Engineering Ethics and Human Values. 2. To understand social responsibility of an engineer. 3. To appreciate ethical dilemma while discharging duties in professional life.

COURSE OUTCOMES: On completion of this course, the students will be able to 1. Understand the significance of value inputs in a classroom and start applying them in their life and

profession 2. Distinguish between values and skills, happiness and accumulation of physical facilities, the Self and the

Body, Intention and Competence of an individual, etc. 3. Understand the role of a human being in ensuring harmony in society and nature. 4. Distinguish between ethical and unethical practices, and start working out the strategy to actualize a

harmonious environment wherever they work.

COURSE CONTENT:

UNIT I: Introduction to Value Education

1. Value Education, Definition, Concept and Need for Value Education. 2. The Content and Process of Value Education. 3. Basic Guidelines for Value Education. 4. Self exploration as a means of Value Education. 5. Happiness and Prosperity as parts of Value Education.

UNIT II: Harmony in the Human Being 1. Human Being is more than just the Body. 2. Harmony of the Self („I‟) with the Body. 3. Understanding Myself as Co-existence of the Self and the Body. 4. Understanding Needs of the Self and the needs of the Body. 5. Understanding the activities in the Self and the activities in the Body.

UNIT III: Harmony in the Family and Society and Harmony in the Nature 1. Family as a basic unit of Human Interaction and Values in Relationships. 2. The Basics for Respect and today‟s Crisis: Affection, e, Guidance, Reverence, Glory,

Gratitude and Love. 3. Comprehensive Human Goal: The Five Dimensions of Human Endeavour. 4. Harmony in Nature: The Four Orders in Nature. 5. The Holistic Perception of Harmony in Existence.

UNIT IV: Social Ethics 1. The Basics for Ethical Human Conduct. 2. Defects in Ethical Human Conduct. 3. Holistic Alternative and Universal Order.

4. Universal Human Order and Ethical Conduct. 5. Human Rights violation and Social Disparities.

UNIT V: Professional Ethics 1. Value based Life and Profession.

2. Professional Ethics and Right Understanding. 3. Competence in Professional Ethics. 4. Issues in Professional Ethics – The Current Scenario. 5. Vision for Holistic Technologies, Production System and Management Models.

TEXT BOOKS 1.A.N Tripathy, New Age International Publishers, 2003. 2.Bajpai. B. L , , New Royal Book Co, Lucknow, Reprinted, 2004 3.Bertrand Russell Human Society in Ethics & Politics

REFERENCE BOOKS 1. Corliss Lamont, Philosophy of Humanism 2. Gaur. R.R. , Sangal. R, Bagaria. G.P, A Foundation Course in Value Education, Excel Books, 2009. 3.Gaur. R.R. , Sangal. R , Bagaria. G.P, Teachers Manual Excel Books, 2009. 4.I.C. Sharma . Ethical Philosophy of India Nagin & co Julundhar 5.Mortimer. J. Adler, - Whatman has made of man 6. William Lilly Introduction to Ethic Allied Publisher

Foreign Language (French)-I Learning Schedule L T P C

2 0 2 3

COURSE DESCRIPTION Basic communication in simple French, Simple conversational phrases, formation of simple sentences, negative sentences, interrogative sentences, simple vocabulary related to house, family, common objects, simple prepositions and conjugation of about 20 verbs.

COURSE CONTENT Unit – I

Getting to know people Starting a conversation People and Things Members of the family Indefinite Article- a, an, one, some Unit – II Arrival Finding a space If you want to ask a Question Pronouns and Verbs Definite Article “The” Formation of negative sentences and questions Unit – III Seeing the Sights Finding your way on foot How do I get to … How to pint out something Verbs Again (Grammar) Conjugation of Verbs ending in “er” –

Parler, Chanter, arriver

Unit – IV Public Transportation What to say to the conductor More action Verbs On Nouns and Articles (grammar) Prepositions Conjugation of Verbs ending in “IR” Demonstrative Adjectives This, That, These, Those Conjugation of Verbs ending in re-Vendre, decendre etc.

Unit – V Numbers - Cardinal, Ordinal Expressing- Time, Conversation regarding Time Days of the week Irregular verbs-Dormir, Partir, sortir, avoir, etreapprendre- comprendre Possessive Adjectives My, Your, His, Their etc.

TEXT BOOK:

1. Barron‟s French The fast and Fun Way. Third Edition

Data Structure and Algorithms using C Learning Schedule L T P C

Pre-requisites: C Programming 3 0 0 3

COURSE DESCRIPTION The purpose of this course is to provide basic concepts of data structures a nd algorithms. The main goal of the course is to teach the students how to select and design data structures for algorithms that are appropriate for problems that they might encounter. This course is also to learn abstracts data types, graphs, tree and its traversal, and different searching and sorting techniques. This also provides knowledge of Hashing techniques and Garbage Collection and Compaction.

COURSE OBJECTIVES The objective of this course is to: 1.Introduce the fundamentals and abstract concepts of Data Structures. 2.Introduce searching, sorting techniques 3.Learn how concepts of data structures are useful in problem solving.

COURSE OUTCOMES At the end of the course student will be able to 1. Use and implement appropriate data structure for the required problems using a programming language such as C/C++. 2. Analyze step by step and develop algorithms to solve real world problems. 3.Implementing various data structures viz. Stacks, Queues, Linked Lists, Trees and Graphs. 4.Understand various searching & sorting techniques.

COURSE CONTENT Unit I: Introduction: Basic Terminology

Elementary Data Organization, Algorithm, Efficiency of an Algorithm, Time and Space Complexity, Asymptotic notations: Big-Oh, Time-Space trade-off. Abstract Data Types (ADT)Arrays: Definition, Single and Multidimensional Arrays, Representation of Arrays : Row Major Order, and Column Major Order, Application of arrays, Sparse Matrices and their representations. Linked lists: Array Implementation and Dynamic Implementation of Singly Linked Lists, Doubly Linked List, Circularly Linked List, Operations on a Linked List. Insertion, Deletion, Traversal, Polynomial Representation and Addition, Generalized Linked List. Unit II: Stacks and Queues: Abstract Data Type Primitive Stack operations: Push & Pop, Array and Linked Implementation of Stack in C, Application of stack: Prefix and Postfix Expressions, Evaluation of postfix expression, Recursion, Tower of Hanoi Problem, Simulating Recursion, Principles of recursion, Tail recursion, Removal of recursion Queues, Operations on Queue: Create, Add, Delete, Full and Empty, Circular queues, Array and linked implementation of queues in C, Dequeue and Priority Queue. Unit III: Trees: Basic terminology Binary Trees, Binary Tree Representation: Array Representation and Dynamic Representation, Complete Binary Tree, Algebraic Expressions, Extended Binary Trees, Array and Linked Representation of Binary trees, Tree Traversal algorithms: Inorder, Preorder and Postorder, Threaded Binary trees, Traversing Threaded Binary trees, Huffman algorithm. Unit IV: Graphs Terminology, Sequential and linked Representations of Graphs: Adjacency Matrices, Adjacency List, Adjacency Multi list, Graph Traversal : Depth First Search and Breadth First Search, Connected Component, Spanning Trees, Minimum Cost Spanning Trees: Prims and Kruskal algorithm. Transitive Closure and Shortest Path algorithm: Warshal Algorithm and Dijikstra Algorithm, Introduction to Activity Networks. Unit V: Searching Sequential search, Binary Search, Comparison and Analysis Internal Sorting: Insertion Sort, Selection,

Bubble Sort, Quick Sort, Two Way Merge Sort, Heap Sort, Radix Sort, Practical consideration for Internal Sorting. Search Trees: Binary Search Trees(BST), Insertion and Deletion in BST, Complexity of Search Algorithm, AVL trees, Introduction to m-way Search Trees, B Trees & B+ Trees Hashing: Hash Function, Collision Resolution Strategies Storage Management: Garbage Collection and Compaction.

TEXT BOOKS

1. Fundamentals of Data Structures - Horowitz and Sahani, Galgotia Publication

REFERENCE BOOKS

1. Data Structures Using C and C++ - Aaron M. Tenenbaum, Yedidyah Langsam and Moshe J. Augenstein, PHI Publications

2. An Introduction to Data Structures with applications - Jean Paul Trembley and Paul G. Sorenson, McGraw Hill Publications

3. Data Structures and Program Design in C - R. Kruse etal, , Pearson Education 4. Data Structures - Lipschutz, Schaum‟s Outline Series, TMH

Computer Architecture & Organization Learning Schedule L T P C

Pre-requisites: Computer Basic 3 0 0 3

COURSE DESCRIPTION This course begins with an introduction to organizational Basic building block diagram of a digital computer system. As the course progresses each major block ranging from Processor to I/O will be discussed in their full architectural detail. The course talks primarily about Computer Organization and Architecture issues, Architecture of a typical Processor, Memory Organization, I/O devices and their interface and System Bus organization etc.

COURSE OBJECTIVES The objective of this course is to:

1. explain the organization of the classical von Neumann machine and its major functional Modules. 2. explain how an instruction is executed in a classical von Neumann machine. 3. provide knowledge of computer system organization and structure through instruction cycles. 4. provide knowledge of system interconnection and the different I/O techniques. 5. explain the basic concepts of interrupts and how interrupts are used to implement I/O control and

data transfers. 6. identify various types of buses in a computer system and illustrate how data transfers is performed.

COURSE OUTCOMES At the end of the course student will be able to:

1. understand and analyze computer architecture and organization, computer arithmetic, and CPU design

2. understand I/O system and interconnection structures of computer 3. understand and analyze different interrupts, I/O techniques, PLDs and memory. 4. incorporate independent learning skills and be able to learn more about different computer

architectures and hardware.

COURSE CONTENT

Unit I: Basic structure of computers

Functional Modules - Basic operational concepts - Bus structures - Software performance – Memory locations and addresses – Memory operations – Instruction and instruction sequencing – Addressing modes – Assembly language – Basic I/O operations– Stacks and queues. Unit II: Arithmetic Module Addition and subtraction of signed numbers – Design of fast adders – Multiplication of positive numbers - Signed operand multi-plication and fast multiplication – Integer division – Floating point numbers and operations. Unit III: Basic processing Module Fundamental concepts – Execution of a complete instruction – Multiple bus organization – Hardwired control – Micro programmed control - Pipelining – Basic concepts – Data hazards – Instruction hazards – Influence on Instruction sets – Data path and control consideration – Superscalar operation. Unit IV: Memory System Basic concepts – Semiconductor RAMs - ROMs – Speed - size and cost – Cache memories - Performance consideration – Virtual memory- Memory Management requirements – Secondary storage. Unit V: PLD, Memories and Logic Families Accessing I/O devices – Interrupts – Direct Memory Access – Buses – Interface circuits – Standard I/O Interfaces (PCI, SCSI, USB).

TEXT BOOKS

1. Computer Organization - Carl Hamacher, Zvonko Vranesic and Safwat Zaky, 5th Edition, McGraw- Hill, 2002.

REFERENCE BOOKS

1. Computer Organisation and Design - Patterson, Elsevier Pub. 2009 2. Computer Organization and Architecture – Designing for Performance - William Stallings, Pearson

Education, 2003. 3. Computer Organization and Design: The hardware / software interface - David A.Patterson and John

L.Hennessy, Morgan Kaufmann, 2002. 4. Computer Architecture and Organization - John P.Hayes, McGraw Hill, 1998.

Discrete Mathematics Learning Schedule

L T P C Pre-requisites: Fundamental of Mathematics 3 0 0 3

COURSE DESCRIPTION The Ideas of Discrete Mathematics are the fundamental to the science and technology specific to the computer age. This subject provides an introduction to some fundamental concepts in Discrete Mathematics for the students. The topics covered include: mathematical logic, proof techniques, especially mathematical induction, set theory, functions, and relations, procedures, recursion, and operation counts, recurrence relations, analysis of algorithms, counting methods, permutations and combinations, graphs and trees.


1. develop a foundation of set theory concepts and notation 2. explore a variety of various mathematical structures by focusing on mathematical

objects, operations, and resulting properties 3. develop formal logical reasoning techniques and notation 4. demonstrate the application of logic to analyzing and writing proofs 5. develop techniques for counting, permutations and combinations 6. develop the concept of relation through various representations (digraphs, matrices, lists).

COURSE OUTCOMES

At the end of the course student will be able to: 1. construct proofs using direct proof, proof by contraposition, proof by contradiction, proof by cases 2. construct mathematical arguments using logical connectives and quantifiers and verify the

correctness of an argument using propositional and predicate logic and truth tables. 3. demonstrate the ability to solve problems using counting techniques and combinatory in the context

of discrete probability. 4. solve problems involving recurrence relations and generating functions. 5. perform operations on discrete structures such as sets, functions, relations and sequence

COURSE CONTENT

Unit I: Set Theory

Introduction, Combination of sets, Multisets, Ordered pairs. Proofs of some general identities on sets. Relations: Definition, Operations on relations, Properties of relations, Composite Relations, Equality of relations, Recursive definition of relation, Order of relations. Functions: Definition, Classification of functions, Operations on functions, Recursively defined functions, Growth of Functions, Natural Numbers: Introduction, Mathematical Induction, Variants of Induction, Induction with Nonzero Base cases. Proof Methods, Proof by counter – example, Proof by contradiction. Unit II: Algebraic Structures Definition, Groups, Subgroups and order, Cyclic Groups, Cosets, Lagrange‟s theorem, Normal Subgroups, Permutation and Symmetric groups, Group Homomorphisms, Definition and elementary properties of Rings and Fields, Integers Modulo n. Unit III: Partial order sets Definition, Partial order sets, Combination of partial order sets, Hasse diagram. Lattices: Definition, Properties of lattices – Bounded, Complemented, Modular and Complete lattice. Boolean Algebra: Introduction, Axioms and Theorems of Boolean algebra, Algebraic manipulation of Boolean expressions. Simplification of Boolean Functions, Karnaugh maps, Logic gates, Digital circuits and Boolean algebra. Unit IV: Propositional Logic Proposition, well-formed formula, Truth tables, Tautology, Satisfiability, Contradiction, Algebra of proposition, Theory of Inference Predicate Logic: First order predicate, well-formed formula of predicate, quantifiers, Inference theory of predicate logic.

Unit V: Trees Definition, Binary tree, Binary tree traversal, Binary search tree. Graphs: Definition and terminology, Representation of graphs, Multigraphs, Bipartite graphs, Planar graphs, Isomorphism and Homeomorphism of graphs, Euler and Hamiltonian paths, Graph coloring Recurrence Relation & Generating function: Recursive definition of functions, Recursive algorithms, Method of solving recurrences. Combinatory, Introduction, Counting Techniques, Pigeonhole Principle

TEXT BOOKS

1. Elements of Distcrete Mathematics - Liu and Mohapatra, McGraw Hill Publications 2. Discrete Mathematical Structures - B. Kolman, R.C. Busby, and S.C. Ross, PHI Publications

REFERENCE BOOKS

1. Discrete Mathematical Structures with Application to Computer Science - Jean Paul Trembley

and R Manohar, McGraw-Hill Publications 2. Discrete and Combinatorial Mathematics - R.P. Grimaldi, Addison Wesley 3. Discrete Mathematics and Its Applications - Kenneth H. Rosen, McGraw-Hill

Digital Electronics Learning Schedule

L T P C Pre-requisites: Physics 3 0 2 4

COURSE OBJECTIVES

1. Understanding the different number systems used in computerized system and codes used to represent the digits and fundamental of arithmetic operation using each number system and codes.

2. Understanding the minimization of logic expression and designing combinational and sequential digital circuits

3. Analyzing the operation and design constraints of CMOS and TTL circuit for logic fabrication. 4. Verifying and analyzing the practical digital circuits. 5. Enabling students to take up application specific sequential circuit to specify the finite state machine

and designing the logic circuit.

COURSE OUTCOMES On completion of this course, the students will be able to

1. Verify and analyze the input/output data of each logic gate and circuits such as adders, counters,

coders, etc,. 2. Analyze the basic operation of memory cell and its limitations in circuit designing. 3. Apply the digital circuit design concept in developing basic component of computer organization,

projects or experiments.

COURSE CONTENT:

Unit I: Number System and Boolean Algebra

Review of number system; types and conversion, codes. Boolean algebra: De-Morgan‟s theorem, switching functions, Prime Implicants and Essential Prime Implicants definition and simplification using K-maps upto 5 variables & Quine McCluskey method. Unit II: Combinational Circuits Introduction to Logic Gates: AND, OR, NOT, NAND, NOR, EX-OR, EX-NOR and their combinations. Design of adder, subtractors, comparators, code converters, encoders, decoders, multiplexers and de- multiplexers, Function realization using gates & multiplexers. Unit III: Synchronous Sequential Ciruits Introduction to Latches and Flip flops - SR, D, JK and T. Design of synchronous sequential circuits – Counters, shift registers. Finite State Machine Design, Mealy, Moore Machines, Analysis of synchronous sequential circuits;, state diagram; state reduction; state assignment with examples. Unit IV: Asynchoronous Sequential Circuits Analysis of asynchronous sequential machines, state assignment, asynchronous design problem. Unit V: PLD, Memories and Logic Families Memories: ROM,RAM, PROM, EPROM, Cache Memories, PLA, PLD, FPGA, digital logic families: TTL, ECL, CMOS.

TEXT BOOKS

1. Mano, Morris. "Digital logic." Computer Design. Englewood Cliffs Prentice-Hall (1979). 2. Kumar, A. Anand. Fundamentals Of Digital Circuits 2Nd Ed. PHI Learning Pvt. Ltd., 2009. 3. Taub, Herbert, and Donald L. Schilling. Digital integrated electronics. New York: McGraw-Hill,

1977. REFERENCE BOOKS

1. Floyd, Thomas L. Digital Fundamentals, 10/e. Pearson Education India, 1986.

2. Malvino, Albert Paul, and Donald P. Leach. Digital principles and applications. McGraw-Hill, Inc., 1986.

3. Jain, Rajendra Prasad. Modern Digital Electronics 3e. Tata McGraw-Hill Education, 2003.

DSA Lab Learning Schedule

L T P C Pre-requisites: C Programming 0 0 2 1


1. Understand Data Structure using C programming Language. 2. Understand DS concept like Stack, Queues, Linked list etc. 3. Understand design principles of Data Structure.

COURSE OUTCOMES

1. At the end of the course student will be able to understand Data Structure. 2. Creating different data structute like Tree, Graph etc.

LIST OF EXPERIMENT (based on):

a. Arrays b. Linked List c. Queues d. Stacks e. Searching Technique

1. Linear Search 2. Binary Search

f. Sorting Technique 1. Selection Sort 2. Insertion Sort 3. Heap Sort 4. Radix Sort etc.

g. Trees h. Graphs

Digital Electronics Lab Learning Schedule L T P C

Pre-requisites: 0 0 2 1

COURSE OBJECTIVES 1. Verifying and analyzing the practical digital circuits. 2. Enabling students to take up application specific sequential circuit to specify the finite state

machine and designing the logic circuit.


1. Verify and analyze the input/output data of each logic gate and circuits such as adders, counters, coders, etc,.

2. Analyze the basic operation of memory cell and its limitations in circuit designing.

LIST OF EXPERIMENT (based on): 1. Logic Gates

a. AND, OR,NOT,XOR,XNOR

2. Flip flops a. SR b. JK c. D-Type Flip flop d. T- Type Flip Flop

3. Registers 4. Counters

Industrial Exposure -I Learning Schedule L T P C

Pre-requisites: Basic knowledge of Computers 0 0 0 1

COURSE OBJECTIVES:

1. To gain industrial exposure through industrial visit in various companies. 2. To experience the discipline of working in a professional organisation and multidisciplinary team. 3. To develop interpersonal, technical and communication skills.

COURSE OUTCOMES

On completion of this component of curriculum, the students will be able to

1. Get exposure to real-life-working environment & practices, and to attain the professionalisms. 2. Work with multi-tasking professionals and multidisciplinary team. 3. To aware about portfolio of industry.

COURSE CONTENT

Industrial visit in various organisation related to respective discipline.

Aptitude Building Learning Schedule L T P C

Pre-requisites: Mathematics 0 0 4 2

COURSE OBJECTIVES: 1. To prepare the students write their project report 2. Get ready to write proposals implementing their ideas 3. To prepare them to speak in Public 4. To make them prepare effective Presentations 5. Enable students in Aptitude building 6. Enable students to use their Aptitude Knowledge effectively in decision making COURSE OUTCOME: 1. Students are trained to write the proposals and assigned projects 2. Students are confident in Public Speaking 3. Students write Presentations on different Industrial topics 4. Improve arithmetic aptitude 5. Learn tricks to solve Aptitude questions faster thereby saving time during competitive exams

COURSE CONTENTS Unit-I Report, Proposal, and Project

Report Writing, Types, Structure, Style and Writing of Reports (on different topics), Characteristics of Report, Categories and Types of Report, Types of Proposal, Nature and Significance, Structure of formal Proposal, Sample Proposal, Writing Proposals on different topics, Difference between Report and Proposal, Project Writing: Essential Features, Structure, Choosing the Subject and Writing the Project on the related Subject. Unit-II: Speaking Skills Group Discussions, Public Speaking, Assertive and Negotiation Strategies. Unit-III: Communication Skills Activities related to Skills required for Engineers (Managerial Skills, Leadership Skills, and Organizational Skills). Unit-IV: Strategies for Recruitment Recruitments and Interviews, Stages in Job Interview, Desirable Qualities, Reviewing the common Question Types of Interviews. Unit-V: Numbers and Arithmetic Basic Classification of Numbers, Divisibility rules –LCM/HCF, Remainders – Base System, Surds, Indices,

Logarithms, Percentage, Profit and Loss, Ratio and Proportion, Approximations, Vedic Maths, Intro to DI, Comprehensive Practice Test on Number system, Percentage and Calculation, Simple Arithmetic: Code-decoding, Analogies, Direction Test, Blood relations ,Comprehension Practice test-1 (Cumulative) ,Comprehension Practice test-2 (Cumulative)

TEXT BOOKS

2. Sanjay Kumar and Pushp Lata „Communication Skills‟, Oxford University Press 2012 3. Raymond Murphy „Essential English Grammar‟, Cambridge University Press 1998 4. Meenakshi Raman and Sangeeta Sharma „Technical Communication Principles and Practice‟,

Oxford University Press 2012. 5. R. K. Narayan, Malgudi Days: A Collection of Short Stories, Penguin 2006 6. Meenakshi Raman and Prakash „Business Communication‟ Oxford University Press 2011

REFERENCE BOOKS

1. Hory Sankar Mukerjee „Business Communication Connecting at Work‟ Oxford University Press 2013.

2. E. Suresh Kumar, P. Sreehari and J. Savithri „Communication Skills and Soft Skills An Integrated Approach‟, Pearson 2012

3. Nitin Bhatnagar and Mamta Bhatnagar „Effective Communication and Soft Skills: Strategies for Success‟, Pearson 2012

4. Francis Peter S. J „Soft Skills and Professional Communication‟, Tata McGraw-Hill 2012 5. Barun K. Mitra „Personality Development and Soft Skills‟, Oxford University Press 2011 6. Dr. Seema Miglani, Shikha Goyal and Rohit Phutela „Communication Skills-II‟, Vayu Education of

India 2009 7. L. Ann Masters and Harold R. Wallace „Personal Development for life and Work‟ Cengage Learning

2012

Technical Skills for Computer Engineers-II Learning Schedule L T P C

Pre-requisites: Fundamental of computers 0 0 2 1

COURSE OBJECTIVES 1. To prepare students to build solid foundation in theory and practice of B.Tech-Computer Science &

Engineering. 2. To make B.Tech-Computer Science & Engineering graduates most competent, industry ready &

competitive in public and private organization 3. To build extensive foundation among students to take up higher study 4. To reduce the industry & academic gap & also train students as per current industry requirement.


1. Develop programs using threads in C 2. Use system calls, low level programming features and threads in C. 3. Write queries in MYSQL. 4. Understand basic concepts of networking, DBMS & compiler 5. Design components of compiler 6. Describe the process of problem solving. 7. Identify and employ techniques for generating possible solutions.

COURSE CONTENT

Unit I: Theory of Automata & Compiler

DFA/NDFA, CFG, Turing m/c, phases of compilers, lexical analysis, parsing Unit II: DBMS & Networking Networking basics: OSI Model, bridge. Router, hub, TCP/IP, Basics of Database, ACID properties, schema, type of data bases, tuple relation algebra, normalization. Unit III: System Programming System calls: get pid, kill, fork, exec, system, wait, zombie process. Use of system call in linux: fchmod, setpriority, getpriority, statfs, other system calls. pthread : Create thread, exiting from thread, joining threads, Thread synchronization: Thread synchronization using semaphores, thread synchronization using mutex Unit IV: MySQL Practicing DML, Simple Select, Char, Number, Date functions, Dual table, : Number Function, Character Function, Set Operations, Aggregate functions, GROUPING, JOINS, Joins, Cartesian product, Views, Sequence Unit V: Problem solving Solving logical problems related to these topics. Clearing students doubts, testing their level of understanding.

TEXT BOOKS

1. Linux system Programming, Love, O reilley 2. Introduction to Automata Theory, Languages, and Computation (3rd Edition) [John E.Hopcroft,

Rajeev Motwani, Jeffrey D. Pearson 3. Computer Networks, Tannenbaum, Pearson 4. Compilers: Principles, Techniques and tools, Aho-Lam-Sethi-Ulman, Pearson 5. Fundamentals of database systems, Elmasari, Navathe, Addison Wesley

REFERENCE BOOKS/LINKS 1. www.tutorialspoint.com/unix_system_calls 2. www.linux-tutorial.info 3. http://www.advancedlinuxprogramming.com/alp-folder/alp-ch08-linux-system-calls.pdf

http://www.tutorialspoint.com/unix_system_calls

http://www.linux-tutorial.info/

http://www.advancedlinuxprogramming.com/alp-folder/alp-ch08-linux-system-calls.pdf

Foreign Language (French)-II Learning Schedule L T P C

Pre-requisites: Foreign Language –I 2 0 2 3

COURSE DESCRIPTION

Conversational Practice, formation of sentences, negative sentences, interrogative sentences, simple vocabulary related to house, family, common objects, simple prepositions and conjugation of Irregular verbs. Writing paragraphs in French.

COURSE CONTENT Unit – 6

Ordinal Numbers Our Travel plans Grammarconjugation of verbs ending in – re, oir Countries and Languages Unit – 7 Weather, Seasons, Months, Days Conjugation of Verbs Irregular verbs Possessive Adjectives Travel by Train Unit - 8 Vouloir and Pouvoir /irregular verbs Meals/ Foods Ordering food Wines, Cheese, Unit - 9 Breakfast, Lunch, Dinner Visit to a Restaurant Unit - 10 Clothing store, Food store Stationary Store

TEXT BOOK:

1. Barron‟s French The fast and Fun Way. Third Edition Mauger: Civilasationet. Langue Francaise.

Psychology and Sociology Learning Schedule L T P C

Pre-requisites: English 2 0 0 2

COURSE DESCRIPTION This course makes the students able to understand and deal with personal and professional aspects of life. They become able to deal with common psychological problems encountered in an engineer‟s life. Their ability to deal with societal aspects of behavior is enhanced. By application of knowledge their quality of personal living and job is maximized.

COURSE OBJECTIVES

1. To sensitize about Psychological and Sociological issues of human life. 2. To make them able to understand and deal with personal and organization phenomenon. 3. Develop an understanding of society as a system of social relationship and various social processes. 4. Develop capacity to analyze social stratification and social change by using relevant theoretical

concepts. 5. To make learners aware of contemporary issues of society.

COURSE OUTCOMES On completion of this course, the students will

1. Be able to understand and deal with personal and organization phenomenon. 2. Be able to deal with common psychological aspects related to an Engineer‟s life. 3. Be able to understand the impact of social environment on individuals, groups and communities. 4. Be able to utilize the knowledge of Sociology and to improve the quality of living of self and social

relationship at large.

CONTENTS Unit I: Psychology: Introduction Definition and Scope of Psychology; Psychology as a science, Personality: Definition, types of personality, Measurement of Personality. Perception, Motivation and Learning.

Unit II: Applications Application of Psychology: Stress-management, Well-being; Self-development: Application of Psychology in building memory and creativity.

Unit III: Sociology: Introduction Importance of Sociology for Engineers, Sociology: Definition and nature; Origin of Society, Social Processes: - Competition, Cooperation Conflict, Accommodation and Assimilation, Social groups – Types and Characteristics; Social Institutions: Marriage: and Family; Religion: Functions and dysfunctions of religion.

Unit IV: Social concerns Social Stratification: Nature and types, Prejudices, Social Mobility. Social Changes: - Urbanization, Westernization, and Pluralism. Social Disorganization, Social Problems: - Deviance, Delinquent behavior amongst youth, Crime, Prostitution, Gender injustice, Child Abuse, Terrorism. Social Movements.

TEXT BOOKS 1. Robbins Stephen, Organizational Behavior. P. Prentice Hall International, Inc. Eaglewood Cliff s, 2005,

ISBN: 0-13- 191435-9 , 11th Edition 2. Eastwood and Atwater, Psychology for living: Adjustment, growth and behavior today. Prentice Hall,

2005, ISBN: 0-13-118117-3, 8th Edition 3. Sharan, Raka, A Hand Book of Sociology ,Anmol Publications, 1995, ISBN: ISBN- 81-7041- 503-1 4. Singh.U.S, Sociology, Priya Books, 1998, ISBN:

REFERENCE BOOKS 1. Meena Hariharan and Radhanath Rath, Coping with life stress. Sage Publications, 2008, ISBN:

0761936556, 10th edition, 2. Dimatto, MR. and Martin, L.R., Health Psychology. Pearson, 2001, ISBN: 0205297773, 10th edition 3. Grace Davie, Sociology of Religion, Sage Publications, 2007, ISBN: 9780761948919 4. Shankar Rao, C .N, Sociology , S.Chand &Co Ltd, 2005, ISBN: 5. Sharma. K.R,Indian Society, Atlantic Publishers, 1997, ISBN:

Numerical Methods and Random process Learning Schedule L T P C

Pre-requisites: Maths 3 1 0 4

COURSE OBJECTIVES: To enhance problem solving skills of engineering students using a powerful problem solving tool namely numerical methods. The tool is capable of handling large systems of equations, nonlinearities and complicated geometries that are common in engineering practice but often impossible to solve analytically.

COURSE OUTCOMES : On completion of this course, the students will be able to

1. Apply various numerical methods and appreciate a trade off in using them. 2. Understand the source of various types of errors and their effect in using these methods. 3. To distinguish between Numerical and Analytical methods along with their Merits and demerits. 4. Understand the use of digital computers in implementation of these methods. 5. Develop a code in C/C++ for the solution of problems that may not be solved by analytical methods.

COURSE CONTENT: Unit-I: Non- Linear Equations and system of Linear Equations

Introduction, error and error propagation, Bisection method, False position Method, Method of Iteration, Newton-Raphson Method, Secant Method, Gauss Elimination method Gauss – Jordan method, Gauss – Seidel method, convergence of iterative methods. Unit-II: Interpolation: Newton‟s Forward and Backward Interpolation, Lagrange‟s Interpolation, Newton‟s Divided Difference Interpolation, Inverse Interpolation. Unit-III : Numerical Differentiation and Integration Derivations from difference tables, Higher order derivations. Newton – Cotes integra-tion formula, Trapezoidal rule, Simpson‟s rule, Boole‟s rule and Weddle‟s rule, Romberg‟s Integration . Unit-IV:Numerical Solution of Ordinary Taylor series method, Euler and modified Euler method, Runge Kutta methods, Milne‟s method, Finite Difference method. Unit-V: Partial Differential Equations Finite difference approximations of partial derivatives, Solution of Laplace‟s equation (Elliptic) by Liebmann‟s iteration method, Solution of one dimensional heat equation (Parabolic) by Bender-Schmidt method and Crank – Nicolson method, Von-Neumann stability condition, Solution of one dimensional wave equation (Hyperbolic), CFL stability condition.

TEXT BOOKS:

1. Introductory Methods of Numerical Analysis: S.S. Sastry, PHI learning Pvt Ltd. REFRENCE BOOKS:

1. Numerical Methods for Scientific and Engineering computation: M.K Jain, S.R.K Iyengar and R.K Jain, New age Inter-national Publishers.

2. Numerical Method: E. Balagurusamy, Tata McGraw Hill Publication.

Object Oriented programming using C++ Learning Schedule L T P C

Pre-requisites: C or any basic language 3 0 0 3

COURSE DESCRIPTION This course introduce programming concept in C++. Students will be equipped with fundamental programming, Arrays, Functions, Exception etc.

COURSE OBJECTIVES 1. introduce the student to the concepts of C++ in computer science. 2. Acquire knowledge to make functions , Files atc

COURSE OUTCOMES 1. Knowledge of programming language. 2. Be aware about OOP‟s concept.. 3. Basic understanding on programming.

COURSE CONTENT Unit I:

Introduction to C++ and Object oriented Concepts C++ Standard Library, Basics of a Typical C++ Environment, Pre-processors Directives, illustrative Simple C++ Programs. Header Files and Namespaces, library files. Introduction to Objects and Object Oriented Programming, Encapsulation (Information Hiding), Access Modifiers: Controlling access to a class, method, or variable (public, protected, private,package), Other Modifiers, Polymorphism: Overloading,Inheritance, Overriding Methods, Abstract Classes, Reusability, Class‟s Behaviors. Unit II:Classes and Data Abstraction: Introduction, Structure Definitions, Accessing Members of Structures, Class Scope and accessing Class Members, Separating Interface from Implementation, Controlling Access Function And Utility Functions, Initializing Class Objects: Constructors, Using Default Arguments With Constructors, Using Destructors, Classes : Const(Constant) Object And Const Member Functions, Object as Member of Classes, Friend Function and Friend Classes, Using This Pointer, Dynamic Memory Allocation with New and Delete, Static Class Members, Container Classes And Integrators, Proxy Classes, Function overloading. Unit III:: Operator Overloading, Inheritance, and Virtual Functions and Polymorphism: Fundamentals of Operator Overloading, Restrictions On Operators Overloading, Operator Functions as Class Members vs. as Friend Functions, Overloading, <<, >> Overloading Unary Operators, Overloading Binary Operators. Introduction to Inheritance, Base Classes And Derived Classes, Protected Members, Casting Base- Class Pointers to Derived- Class Pointers, Using Member Functions, Overriding Base – Class Members in a Derived Class, Public, Protected and Private Inheritance, Using Constructors and Destructors in derived Classes, Implicit Derived –Class Object To Base- Class Object Conversion, Composition Vs. Inheritance. Introduction to Virtual Functions, Abstract Base Classes And Concrete Classes, Polymorphism, New Classes And Dynamic Binding, Virtual Destructors, Polymorphism, Dynamic Binding. Unit IV:: Files and I/O Streams and Templates and Exception Handling: Files and Streams, Creating a Sequential Access File, Reading Data From A Sequential Access File, Updating Sequential Access Files, Random Access Files, Creating A Random Access File, Writing Data Randomly To a Random Access File, Reading Data Sequentially from a Random Access File. Stream Input/Output Classes and Objects, Stream Output, Stream Input, Unformatted I/O (with read and write), Stream Manipulators, Stream Format States, Stream Error States. Function Templates, Overloading Template Functions, Class Template, Class Templates and Non-Type Parameters, Templates and Inheritance, Templates and Friends, Templates and Static Members. Introduction, Basics of C++ Exception Handling: Try Throw, Catch, Throwing an Exception, Catching an Exception, Rethrowing an Exception, Exception specifications, Processing Unexpected Exceptions, Stack Unwinding, Constructors, Destructors and Exception Handling, Exceptions and Inheritance.

TEXT BOOKS:

1. C++ How to Program by H M Deitel and P J Deitel, 1998, Prentice Hall 2. Object Oriented Programming in Turbo C++ by Robert Lafore, 1994, The WAITE Group Press. 3. Programming with C++ By D Ravichandran, 2003, T.M.H

REFERENCE BOOKS:

1. Object oriented Programming with C++ by E Balagurusamy, 2001, Tata McGraw-Hill 2. Computing Concepts with C++ Essentials by Horstmann, 2003, John Wiley, 3. The Complete Reference in C++ By Herbert Schildt, 2002, TMH


Learning Schedule L T P C


COURSE DESCRIPTION This course provides the design of database application systems through a mini project and to get some practical hand-on experience with commercial database management systems by writing application programs using the DBMS query languages. It offers students an introduction to the design and programming of database systems. It also covers the ER (entity-relationship) approach to data modeling, the relational model of database management systems (DBMSs) and the use of query languages such as SQL. Lecture also covers the relational algebra and the use of SQL in a programming environment.

COURSE OBJECTIVES

1. Knowledge of DBMS, in terms of use and implementations. 2. Experience with analysis and design of various database softwares (SQL/PL-SQL, Forms, Reports,

DBA, DBM) in order to manage a large complex database systems. 3. Understand the concept of data planning and database design for serving different types of users with

varying skill levels. 4. Handling different user views of the same stored data, combining interrelated data setting standards,

controlling concur-rent updates so as to maintain data integrity. 5. Managing, planning and coordinating restart and recovery operations across multiple users for a

large complex systems.

COURSE OUTCOMES 1. Understand the relational database theory, and be able to write relational algebra expressions for

queries, logical design of databases, including the E‐ R method and normalization approach. 2. Illustrate commercial relational database system by writing SQL. 3. Understand the relational database theory, and be able to write relational algebra expressions for

queries, logical design of databases, including the E‐ R method and normalization approach. 4. Understand and analyze the database storage structures and access techniques like file and page

organizations, indexing methods including B‐ tree, hashing, query evaluation techniques and and query optimization.

5. Understand various issues of transaction processing and concurrency control by designing and development of a database application system as part of a team.

COURSE CONTENT Unit I: Introduction

An overview of database management system, database system vs file system, Database system concept and architecture, data model schema and instances, data independence and database language and interfaces, data definitions language, DML, Overall Database Structure. Data modeling using the Entity Relationship Model: ER model concepts, notation for ER diagram, mapping constraints, keys, Concepts of Super Key, candidate key, primary key, Generalization, aggregation, reduction of an ER diagrams to tables, extended ER model, relationship of higher degree. Unit II: Relational data Model and Language Relational data model concepts, integrity constraints, entity integrity, referential integrity, Keys constraints, Domain constraints, relational algebra, relational calculus, tuple and domain calculus. Introduction on SQL: Characteristics of SQL, advantage of SQL. SQL data type and literals. Types of SQL commands. SQL operators and their procedure. Tables, views and indexes. Queries and sub queries. Aggregate functions. Insert, update and delete operations, Joins, Unions, Intersection, Minus, Cursors, Triggers, Procedures in SQL/PL SQL. Unit III: Data Base Design & Normalization Functional dependencies, normal forms, first, second, third normal forms, BCNF, inclusion dependence, loss less join decompositions, normalization using FD, MVD, and JDs, alternative approaches to database design.

Unit IV: Transaction Processing Concept Transaction system, Testing of serializability, serializability of schedules, conflict & view serializable schedule, recoverability, Recovery from transaction failures, log based recovery, checkpoints, deadlock handling. Distributed Database: distributed data storage, concurrency control, directory system. Unit V: Concurrency Control Techniques Concurrency control, Locking Techniques for concurrency control, Time stamping protocols for concurrency control, validation based protocol, multiple granularity, Multi version schemes, Recovery with concurrent transaction, case study of Oracle/DB2.

TEXT BOOKS

1. Fundamentals of Database Systems – Elmasri and Navathe, Addision Wesley 2. An Introduction to Database Systems - Date C J, Addision Wesley

REFERENCE BOOKS

1. Database Concepts - Korth, Silbertz and Sudarshan, McGraw Hill 2. Database Management Systems - Leon & Leon, Vikas Publishing House 3. An Introduction to Database Systems - Bipin C. Desai, Galgotia Publications 4. Database Management System - Majumdar and Bhattacharya, TMH 5. Database Management System – Ramkrishnan and Gehrke, McGraw Hill 6. Database Processing Fundamentals, Design and Implementation - Kroenke, Pearson Education.

Operating System Learning Schedule L T P C

Pre-requisites: Computer Architecture 3 0 0 3

COURSE DESCRIPTION This course provides fundaments of operating systems. This course includes concurrency, processes, threads, context switching, synchronization, deadlock, CPU scheduling memory management and virtual memory. It also includes file systems, storage devices, disk management and scheduling, directories, protection, and crash recovery. COURSE OBJECTIVES

1. Learn fundamental operating system abstractions such as processes, threads, files, semaphores, IPC abstractions, shared memory regions, etc.,

2. Learn how the operating system abstractions can be used in the development of application programs, or to build higher level abstractions,

3. Learn how the operating system abstractions can be implemented, 4. Learn the principles of concurrency and synchronization, and apply them to write correct concurrent

programs/software, 5. Learn basic resource management techniques (scheduling, time management, space management)

and principles and how they can be implemented. These also include issues of performance and fairness objectives, avoiding deadlocks, as well as security and protection.

COURSE OUTCOMES 1. Understand and identify the System calls, protection, interrupts. 2. Understand Input/Output, Process, disk accesses, file systems. 3. Understand the concepts of Virtual memory and how it is realized in system. 4. Implement Concurrency & synchronization Semaphores/monitors, shared memory,

mutual exclusion Process scheduling services. COURSE CONTENT Unit I: Introduction

Operating system and functions, Classification of Operating systems- Batch, Interactive, Time sharing, Real Time System, Multiprocessor Systems, Multiuser Systems, Multiprocess Systems, Multithreaded Systems, Operating System Structure- Layered structure, System Components, Operating System services, Reentrant Kernels, Monolithic and Microkernel Systems. Unit II: Concurrent Processes Process Concept, Principle of Concurrency, Producer / Consumer Problem, Mutual Exclusion, Critical Section Problem, Dekker‟s solution, Peterson‟s solution, Semaphores, Test and Set operation; Classical Problem in Concurrency- Dining Philosopher Problem, Sleeping Barber Problem; Inter Process Communication models and Schemes, Process generation. Unit III: CPU Scheduling Scheduling Concepts, Performance Criteria, Process States, Process Transition Diagram, Schedulers, Process Control Block (PCB), Process address space, Process identification information, Threads and their management, Scheduling Algorithms, Multiprocessor Scheduling. Deadlock: System model, Deadlock characterization, Prevention, Avoidance and detection, Recovery from deadlock. Unit IV: Memory Management Memory Management: Basic bare machine, Resident monitor, Multiprogramming with fixed partitions, Multiprogramming with variable partitions, Protection schemes, Paging, Segmentation, Paged segmentation, Virtual memory concepts, Demand paging, Performance of demand paging, Page replacement algorithms, Thrashing, Cache memory organization, Locality of reference. Unit V: Input/ Output I/O Management and Disk Scheduling: I/O devices, and I/O subsystems, I/O buffering, Disk storage and disk scheduling, RAID. File System: File concept, File organization and access mechanism, File directories,

and File sharing, File system implementation issues, File system protection and security. TEXT BOOKS

1. Operating Systems Concepts - Silberschatz, Galvin and Gagne,Wiley Publications 2. Operating Systems: A Concept based Approach - D M Dhamdhere, 2nd Edition.

REFERENCE BOOKS

1. Operating Systems - Sibsankar Halder and Alex A Aravind, Pearson Education 2. An Introduction to Operating System - Harvey M Dietel, Pearson Education

Computer Graphics Learning Schedule L T P C

Pre-requisites: C Language 3 0 0 3

COURSE DESCRIPTION This course focuses on 2D and 3D interactive and non-interactive graphics. This course studies the principles underlying the generation and display of 2D and 3D computer graphics. In this course topics include geometric modeling, 3D viewing and projection, lighting and shading, color, and the use of one or more technologies and packages such as OpenGL, and Blender. Course requirements usually include exam and several programming or written homework assignments.

COURSE OBJECTIVES 1. To provide a comprehensive introduction to computer graphics leading to the ability to understand

contemporary terminology, progress, issues, and trends. 2. To understand computer graphics techniques (2-D/3-D), focusing on 3D modelling, image synthesis,

and rendering. 3. Introduce geometric transformations, geometric algorithms, software systems (OpenGL), 3D object

models (surface, volume and implicit), visible surface algorithms, image synthesis, shading and mapping, ray tracing, radiosity, global illumination, photon mapping, and anti-aliasing.

4. To explore the interdisciplinary nature of computer graphics which is emphasized in the wide variety of examples and applications.

COURSE OUTCOMES 1. To develop a facility with the relevant mathematics of computer graphics, e.g., 3D rotations using

both vector algebra, geometrical transformations and projections using homogeneous co-ordinations. 2. Apply principles and techniques of computer graphics, e.g., the graphics pipeline, and Bresenham

algorithm for speedy line and circle generation. 3. Apply computer graphics concepts in the development of computer games, information

visualization, and business applications. COURSE CONTENT Unit I: Introduction and Line Generation

Types of computer graphics, Graphic Displays- Random scan displays, Raster scan displays, Frame buffer and video controller, Points and lines, Line drawing algorithms, Circle generating algorithms, Midpoint circle generating algorithm, and parallel version of these algorithms. Unit II: Transformations Basic transformation, Matrix representations and homogenous coordinates, Composite transformations, Reflections and shearing. Windowing and Clipping: Viewing pipeline, Viewing transformations, 2-D Clipping algorithms-Line clipping algorithms such as Cohen Sutherland line clipping algorithm, Liang Barsky algorithm, Line clipping against nonrectangular clip windows; Polygon clipping – Sutherland Hodgeman polygon clipping, Weiler and Atherton polygon clipping, Curve clipping, Text clipping. Unit III: Three Dimensional

geometric primitives, 3-D Object representation, 3-D Transformation, 3-D viewing, projections, 3-D Clipping.

Unit IV: Curves and Surfaces Quadric surfaces, Spheres, Ellipsoid, Blobby objects, introductory concepts of Spline, Bspline and Bezier curves and surfaces. Unit V: Hidden Lines and Surfaces Back Face Detection algorithm, Depth buffer method, A- buffer method, Scan line method, basic illumination models – Ambient light, Diffuse reflection, Specular reflection and Phong model, Combined approach, Warn model, Intensity Attenuation, Color consideration, Transparency and Shadows.

TEXT BOOKS

1. Computer Graphics C Version - Donald Hearn and M Pauline Baker, Pearson Education

REFERENCE BOOKS

1. Computer Graphics - Amrendra N Sinha and Arun D Udai, TMH Publications 2. Computer Graphics: A Programming Approach - Steven Harrington, TMH Publications 3. Procedural Elements of Computer Graphics - Rogers, McGraw Hill

OOP’s Lab Learning Schedule

L T P C Pre-requisites: C Language 0 0 2 1


4. Understand the C++ programming Language. 5. Understand OOP‟s concept like Inheritance, Abstraction etc.. 6. Understand design principles of Object programming

COURSE OUTCOMES

3. At the end of the course student will be able to: 4. Creating C++ File 5. Creating Functions, Template eetc.

LIST OF EXPERIMENT (based on):

a. Functions b. Arrays c. Pointers d. This pointer e. Friend Function f. Virtual Function g. Abstract Class h. Inheritance i. Operator Overloading j. File Handling k. Template l. Handling of Exceptions

Database Management System Lab Learning Schedule L T P C

Pre-requisites: SQL 0 0 2 1


7. Understand the relational database theory, and write relational algebra expressions for queries, logical design of databases, including the ER method and normalization approach.

8. Understand various issues of transaction processing and concurrency control by designing and development of a database application system as part of a team.

9. Understand design principles for logical design of databases, including the ER method and normalization approach.

COURSE OUTCOMES

6. At the end of the course student will be able to: 7. Creating database objects 8. Modifying database objects and manipulating the data 9. Retrieving the data from the database server 10. Performing database operations in a procedural manner using pl/sql 11. Design and Develop applications like banking, reservation system, etc.

LIST OF EXPERIMENT:

1. Write the queries for Data Definition and Data Manipulation Language. 2. Write SQL queries using Comparison operators (=,<,>,etc). 3. Write SQL queries using Logical operators. 4. Write SQL query using SQL Operators. 5. Write SQL queries for relational algebra. 6. Write SQL queries for extracting data from more than one table. 7. Write SQL queries for sub queries, nested queries. 8. Write programme by the use of PL/SQL. 9. Concepts for ROLL BACK, COMMIT & CHECK POINTS. 10. Create VIEWS, CURSORS and TRGGERS & write ASSERTIONS. 11. Create FORMS and REPORTS.

Computer Graphics Lab Learning Schedule L T P C


COURSE OBJECTIVES: The objective of this course is:

1. to make student able to implement the computer graphics algorithm and basic animation using „C‟.

COURSE OUTCOMES: 1. At the end of the course student will be able to Switch between graphics modes and text mode. 2. Implement line, circle and ellipse drawing algorithms, 3. Apply simple and composite transformations on graphics objects/elements. Implement filling

algorithms, line and polygon clipping algorithms and create animations.

LIST OF EXPERIMENT: Write a program for:

1. Line Drawing Algorithms 2. Circle Drawing Algorithms 3. Ellipse Drawing Algorithms 4. Polygon Filling Algorithms 5. Basic Transformations 6. Composite Transformations 7. Line Clipping Algorithms 8. Polygon Clipping Algorithms 9. Curve Generations 10. Animation

Industrial Training -I Learning Schedule L T P C


COURSE OBJECTIVES:

4. To gain first-hand experience of working as an engineering professional,including the technical application of engineering knowledge.

5. To experience the discipline of working in a professional organisation and multidisciplinary team. 6. To develop technical, interpersonal and communication skills.

COURSE OUTCOMES


4. Apply engineering knowledge in solving real-life problems. 5. Attain new skills and be aware of the state-of-art in engineering disciplines of their own interest. 6. Get exposure to real-life-working environment & practices, and to attain the professionalisms. 7. Work with multi-tasking professionals and multidisciplinary team. 8. Prepare a technical report, to improve presentation and other soft skills.

COURSE CONTENT Exposure to real life problems at various reputed industries engaged in areas of Computer Science and Engineering.

Personality & Career Building Learning Schedule

L T P C Pre-requisites: Adaptive and punctual 0 0 4 2

COURSE OBJECTIVES: 1. Holistic approach focusing on 2. Negotiation skills 3. Team work 4. Balancing the emotional Quotient of the individuals 5. Ready to apply for a job 6. Skill development related to classification of numbers 7. Implementing logical Aptitude in decision making

COURSE OUTCOMES: 1. Get an idea of industry perspective 2. Give the Effective Presentation 3. Able to develop a logical thought process related to every aspect of life 4. Able to widen the horizon of one‟s thought process and data analysis skills 5. Able to interpret Data and convert into information

COURSE CONTENT Unit-I: Strategies and Skills Required for Career building/ Recruitment/ Team building

Learning of Different Strategies to be used: Negotiation, Assertions, Politeness through Conversation, Assertive Strategies, Leadership Skills, Team Work, Management Skills through Group Activities. Unit-II: Group Discussions and Role Play Listening and Speaking Comprehensions through Group Discussion and audio-visual aids, Do‟s and Don‟ts of Group Discussions related to various topics (Day-Today life/ Social Issues/ Political and Others. Unit-III: Business/job Correspondence Resume Writing, Letter Writing, Job Application Letter Unit-IV: Time and Work, Data Interpretation Time and Work ,Time speed and Distance, Table, Line Graph, Bar Graph,Cube,Dice,Calendars,Test on Bar and Pie Charts, Comprehensive Practice test- 1 on Area Covered, Comprehensive Practice test- 2 on Area Covered. Unit-V: Algebra and Simple Reasoning Linear and Quadratic Equation, Function Basics, Inequalities, Progression, Set Theory/ Venn diagram, Pie Chart, Permutation and Combination, Probability, Visual Reasoning, Alphabet based Reasoning, Comprehensive Practice test- 1 on Area Covered, Comprehensive Practice test- 2 on Area Covered. TEXT BOOKS:

1. Sanjay Kumar and Pushp Lata „Communication Skills‟, Oxford University Press 2012 2. Raymond Murphy „Essential English Grammar‟, Cambridge University Press 1998 3. Meenakshi Raman and Sangeeta Sharma „Technical Communication Principles and Practice‟,

Oxford University Press 2012. REFERENCE BOOKS

1. R. K. Narayan, Malgudi Days: A Collection of Short Stories, Penguin 2006 2. Meenakshi Raman and Prakash „Business Communication‟ Oxford University Press 2011 3. Hory Sankar Mukerjee „Business Communication Connecting at Work‟ Oxford University Press

2013

Technical Skills for Computer Engineers-III Learning Schedule L T P C


COURSE OBJECTIVES

1. To prepare a strong foundation for basics of Computer Science 2. To improve OOPS programming skills 3. To enable them to understand working of computer hardware and software


1. Compare different computer architecture based upon their performance 2. Use complex data structure in engineering problems. 3. Develop programs using OOPs concept. 4. Understand mathematical concepts necessary for designing computers systems

COURSE CONTENT Unit I: Automata & Compiler:

DFA/NDFA, CFG/Turing m/c, phases of compilers, lexical analysis, parsing Unit II: Computer Architecture & O.S.

Computer organizations (Accumulator based/ General purpose register based/stack based), Addressing mode, RISC/CISC, Control Unit: Hardwired control unit, micro programmed control unit, Memory, RAM, Cache memory, Mapping techniques (Direct/associative, set associative), hit ratio , Pipeline concepts, speedup, hazards: data hazards, control hazards, structural Unit III: Networking & OS Networking basics: OSI Model, bridge. Router, hub, TCP/IP, Operating systems Basics: Process and threads, CPU scheduling, process synchronization, memory management Unit IV: OOPS & DAA OOPS basics: Data abstraction, class, objects, inheritance, polymorphism, operator overloading. Design and analysis of algorithms: Asymptotic complexity notations, divide and conquer, recursion, dynamic programming, greedy approach Unit V: DBMS & Software Engineering Basics of Database, ACID properties, schema, type of data bases, tuple relation algebra, and normalization. Software Engineering: Life cycle, cyclomatic complexity, black box/white box testing, test case generation, software cost estimation TEXT BOOKS:

1. Computer System Organization, Morris Mano, PHI 2. Introduction to Automata Theory, Languages, and Computation (3rd Edition) [John E.Hopcroft,

Rajeev Motwani, Jeffrey D. Pearson 3. Computer Networks, Tannenbaum, Pearson

REFERENCE BOOKS 1. Operating system concepts, Silberschatz, Galvin, Willey 2. Compilers: Principles, Techniques and tools, Aho-Lam-Sethi-Ulman, Pearson 3. Fundamentals of database systems, Elmasari, Navathe, Addison Wesley 4. Software Engineering, K.K. Agrawal & Yogesh Singh, New Age International

Entrepreneurship Development Learning Schedule L T P C


COURSE OBJECTIVES:

The objective of the section is to develop conceptual understanding of the topic among the students and comprehend the environment of making of an Entrepreneur. Specific topics to be covered in the section are as follows:

COURSE OUTCOMES 1. To inculcate entrepreneurship skills to students. 2. To aware about industry structure and how to start up a company

COURSE CONTENT Unit I : Entrepreneurship

Definition, requirements to be an entrepreneur, entrepreneur and intrapreneur, entrepreneur and manager, growth of entrepreneurship in India, women entrepreneurship, rural and urban entrepreneurship. Unit II : Entrepreneurial Motivation Motivating factors, motivation theories-Maslow‟s Need Hierarchy Theory, McClelland‟ s Acquired Need Theory, government‟s policy actions towards entrepreneurial motivation, entrepreneurship development programmes. Unit III : Types of Enterprises and Ownership Structure: Small scale, medium scale and large scale enterprises, role of small enterprises in economic development; proprietorship, partnership, Ltd. companies and co-operatives: their formation, capital structure and source of finance. Unit IV: Projects: Identification and selection of projects; project report: contents and formulation, concept of project evaluation, methods of project evaluation: internal rate of return method and net present value method. Unit V: Management of Enterprises Objectives and functions of management, scientific management, general and strategic management; introduction to human resource management: planning, job analysis, training, recruitment and selection, etc.; marketing and organizational dimension of enterprises; enterprise financing : raising and managing capital, shares, debentures and bonds, cost of capital; break- even analysis, balance sheet its analysis.. Institutional Support and Policies: institutional support towards the development of entrepreneurship in India, technical consultancy organizations, government policies for small scale enterprises.

TEXT BOOKS:

1. Ram Chandran, „Entrepreneurial Development‟, Tata McGraw Hill, New Delhi 2. Saini, J. S., „Entrepreneurial Development Programmes and Practices‟ , Deep & Deep

Publications (P), Ltd. 3. Khanka, S S. „Entrepreneurial Development‟, S Chand & Company Ltd. New Delhi

REFERENCE BOOKS:

1. Badhai, B „Entrepreneurship for Engineers‟, Dhanpat Rai & co. (p) Ltd. 2. Desai, Vasant, „ Project Management and Entrepreneurship‟, Himalayan Publishing House,

Mumbai, 2002. 3. Gupta and Srinivasan, „Entrepreneurial Development‟, S Chand & Sons, New Delhi.

Computer Networks Learning Schedule

L T P C Pre-requisites: CAO and DE 3 0 0 3

COURSE DESCRIPTION This course primarily aims to acquaint the student with basic computer and communication networking technologies and the layered approach that makes design, implementation and operation of computer and communication networks possible. It also describe the complete study of OSI model which includes application layer: HTTP,FTP, SMTP, POP3, and peer-to-peer applica-tions, transport layer: UDP, TCP and congestion control, network layer: switches, routers, IP protocols and routing algorithms, link layer: error detection and correction, multiple access, MAC addressing, etc. Upon completion of this course, student should have complete knowledge about computer network related hardware and software using a layered architecture.


1. Discuss the evolution of computer network concepts. 2. Understand the structure of computer networks, factors affecting computer network deployment. 3. Describe emerging technology in the net-centric computing area and assess their current

capabilities, limitations and potential applications. 4. Program and analyse network protocols, architecture, algorithms and other safety critical issues in

real-life scenario.

COURSE OUTCOMES At the end of course the student will be able to:

1. Examine and analyze various protocols like transport-layer concepts: Transport-Layer services -

Reliable vs. un-reliable data transfer -TCP protocol -UDP protocol 2. Examine and analyze the network-layer concepts like Network-Layer services –Routing -IP protocol

-IP addressing 3. Examine and analyze the different link-layer and local area network concepts like Link-Layer

services –Ethernet -Token Ring -Error detection and correction -ARP protocol 4. Analyze and implement application of network system.

COURSE CONTENT Unit I: Introduction Concepts

Goals and Applications of Networks, Network structure and architecture, The OSI reference model, services, Network Topology Design - Delay Analysis, Back Bone Design, Local Access Network Design, Physical Layer Transmission Media, Switching methods, ISDN, Terminal Handling. Unit II: Medium Access sub layer Medium Access sub layer - Channel Allocations, LAN protocols -ALOHA protocols - Overview of IEEE standards - FDDI. Data Link Layer - Elementary Data Link Protocols, Sliding Window protocols, Error Handling. Unit III: Network Layer Network Layer - Point - to Pont Networks, routing, Congestion control Internetworking -TCP / IP, IP packet, IP address, IPv6. Unit IV: Transport Layer Transport Layer - Design issues, connection management, session Layer-Design issues, remote procedure call. Presentation Layer-Design issues, Data compression techniques, cryptography - TCP - Window Management. Unit V: Application Layer File Transfer, Access and Management, Electronic mail, Virtual Terminals, Other application. Example Networks- Internet and Public Networks.

TEXT BOOKS 1. Forouzen, “Data Communication and Networking”, TMH

REFERENCE BOOKS

1. A.S. Tanenbaum, Computer Networks, Pearson Education 2. W. Stallings, Data and Computer Communication, Macmillan Press 3. Anuranjan Misra, “Computer Networks”, Acme Learning 4. G. Shanmugarathinam, ”Essential of TCP/ IP”, Firewall Media

Analysis and Design of Algorithms Learning Schedule L T P C

Pre-requisites: Fundamental of C 3 0 0 3

COURSE DESCRIPTION This course provides elementary introduction to algorithm design and analysis. It includes the topic: mathematics foundation, divided-and-conquer, dynamic programming, greedy method, NP-completeness complexity, approximation algorithm, random-ized algorithm, etc. At the end of this course student should be able to understand the concepts and skills of algorithm design, Implemental some well-known algorithms and analyze the performance of algorithms . COURSE OBJECTIVES The objective of this course is to learn:

1. Existing algorithm and develop efficient algorithms for simple computational tasks. 2. Reasoning about the correctness of the algorithm 3. Behaviours of algorithms and the notion of tractable and intractable problems.


1. Analyze algorithms and determine efficiency of algorithm. 2. Understand advanced abstract data type (ADT), data structures and their implementations 3. Design algorithms using the brute force, greedy, divide and conquer, branch and bound etc.

methodologies. 4. Prove problems of P, NP, or NP-Complete. 5. Develop and implement learned/new algorithm using appropriate techniques to solve problems.


Introduction : Algorithms, Analyzing algorithms, Complexity of algorithms, Growth of functions, Performance measurements, Sorting and order Statistics - Shell sort, Quick sort, Merge sort, Heap sort, Comparison of sorting algorithms, Sorting in linear time. Unit II: Advanced Data Structures Advanced Data Structures: Red-Black trees, B – trees, Binomial Heaps, Fibonacci Heaps. Unit III : Divide & Conquer and Greedy Methods Divide and Conquer with examples such as Sorting, Matrix Multiplication, Convex hull and Searching. Greedy methods with examples Huffman Coding, Knapsack, Minimum Spanning trees – Prim‟s and Kruskal‟s algorithms, Single source shortest paths - Dijkstra‟s and Bellman Ford algorithms. Unit IV: Dynamic Programming Dynamic programming with examples such as Knapsack, All pair shortest paths –Warshal‟s and Floyd‟s algorithms, Resource allocation problem. Backtracking, Branch and Bound with examples such as Travelling Salesman Problem, Graph Coloring, n-Queen Problem, Hamiltonian Cycles and Sum of subsets. Unit V Algebraic computation, String Matching, Theory of NP-completeness, Approximation algorithms and Randomized algorithms.

TEXT BOOKS

1. Thomas H. Coreman, Charles E. Leiserson and Ronald L. Rivest, “Introduction to Algorithms”, Printice Hall of India.

REFERENCE BOOKS

1. RCT Lee, SS Tseng, RC Chang and YT Tsai, “Introduction to the Design and Analysis of

Algorithms”, Mc Graw Hill, 2005. 2. E. Horowitz & S Sahni, “Fundamentals of Computer Algorithms”, 3. Berman, Paul,” Algorithms”, Cengage Learning. 4. Aho, Hopcraft, Ullman, “The Design and Analysis of Computer Algorithms” Pearson Education,

2008.

Compiler Design Learning Schedule L T P C

Pre-requisites: OS and CAO 3 1 0 4

COURSE DESCRIPTION The goal of the course is to provide an introduction to the system software like assemblers, compilers, and macros. It provides the complete description about inner working of a compiler. This course focuses mainly on the design of compilers and optimization techniques. It also includes the design of Compiler writing tools. This course also aims to convey the language specifications, use of regular expressions and context free grammars behind the design of compiler.


1. Provide an understanding of the fundamental principles in compiler design 2. Provide the skills needed for building compilers for various situations that one may

encounter in a career in Computer Science. 3. Learn the process of translating a modern high-level language to executable code required for

compiler construction.

COURSE OUTCOMES At the end of course students will be able to:

1. Understand fundamentals of compiler and identify the relationships among different phases of the compiler.

2. Understand the application of finite state machines, recursive descent, production rules, parsing, and language semantics.

3. Analyze & implement required module, which may include front-end, back-end, and a small set of middle-end optimizations.

4. Use modern tools and technologies for designing new compiler.


Introduction to Compiler, Phases and passes, Bootstrapping, Finite state machines and regularexpressions and their applications to lexical analysis, Optimization of DFA-Based PatternMatchers implementation of lexical analyzers, lexical-analyzer generator, LEX-compiler,Formal grammars and their application to syntax analysis, BNF notation, ambiguity, YACC.The syntactic specification of programming languages: Context free grammars, derivation andparse trees, capabilities of CFG.

Unit II: Basic Parsing Techniques Parsers, Shift reduce parsing, operator precedence parsing, top down parsing, predictive parsers Automatic Construction of efficient Parsers: LR parsers, the canonical Collection of LR (0) items, constructing SLR parsing tables, constructing Canonical LR parsing tables, Constructing LALR parsing tables, using ambiguous grammars, an automatic parser generator, and implementation of LR parsing tables.

Unit III: Syntax-directed Translation Syntax-directed Translation schemes, Implementation of Syntax directed Translators, Intermediate code, postfix notation, Parse trees & syntax trees, three address code, quadruple & triples, translation of assignment statements, Boolean expressions, statements that alter the flow of control, postfix translation, translation with a top down parser. More about translation: Array references in arithmetic expressions, procedures call, declaration sand case statements.

Unit IV: Symbol Tables

Data structure for symbols tables, representing scope information. Run-Time Administration: Implementation of simple stack al-location scheme, storage allocation in block structured language. Error Detection & Recovery: Lexical Phase errors, syntactic phase errors semantic errors.

Unit V: Code Generation Selected Topics: Algebraic Computation, Fast Fourier Transform, String Matching, Theory of NP- completeness, Approximation algorithms and Randomized algorithms. . TEXT BOOKS

1. ALFRED V AUTOR AHO, JEFFREY D AUTOR ULLMAN “Principles of Compiler Design”. 2. V Raghvan, “ Principles of Compiler Design”, TMH 3. Kenneth Louden,” Compiler Construction”, Cengage Learning.

REFERENCE BOOKS

1. Aho, Sethi & Ullman, “Compilers: Principles, Techniques and Tools”, Pearson Education2 2. Charles Fischer and Ricard LeBlanc,” Crafting a Compiler with C”, Pearson Education

E-Commerce Learning Schedule

L T P C Pre-requisites: Web development 3 0 0 3

COURSE DESCRIPTION This course introduces the concepts, vocabulary, and procedures associated with E-Commerce and the Internet. The student gains an overview of all aspects of E-Commerce. Topics include development of the Internet and E-Commerce, options available for do-ing business on the Internet, features of Web sites and the tools used to build an E-Commerce web site, marketing issues, payment options, security issues, and customer service.


1. Discuss fundamentals of e-commerce, types and applications. 2. Evaluate the role of the major types of information systems in a business environment and their

relationship to each other 3. Assess the impact of the Internet and Internet technology on business electronic commerce and

electronic business 4. Identify the major management challenges for building and using information systems and learn how

to find appropriate solutions to those challenges. 5. Learn strategies for e-commerce, Mobile Commerce, Wireless Application Protocol, WAP technology and

Mobile Information devices.


1. Understand the basic concepts and technologies used in the field of management information

systems 2. Understand the processes of developing and implementing information systems 3. Be aware of the ethical, social, and security issues of information systems and 4. Develop an understanding of how various information systems work together to accomplish the

information objectives of an organization 5. Understand the role of information systems in organizations, the strategic management processes,

and the implications for the management and learn about the importance of managing organizational change associated with information systems implementation

COURSE CONTENT Unit I: INTRODUCTION Definition of Electronic Commerce, E-Commerce: technology and prospects, incentives for engaging in electronic commerce, needs of E-Commerce, advantages and disadvantages, framework, Impact of E- commerce on business, E-Commerce Models.

Unit II: NETWORK INFRASTRUCTURE FOR E- COMMERCE Internet and Intranet based E-commerce- Issues, problems and prospects, Network Infrastructure, Network Access Equipments, Broadband telecommunication (ATM, ISDN, FRAME RELAY). Mobile Commerce: Introduction, Wireless Application Protocol, WAP technology, Mobile Information device.

Unit III: WEB SECURITY Security Issues on web, Importance of Firewall, components of Firewall, Transaction security, Emerging client server, Security Threats, Network Security, Factors to consider in Firewall design, Limitation of Firewalls.

Unit IV: ENCRYPTION

Encryption techniques, Symmetric Encryption: Keys and data encryption standard, Triple encryption, Secret key encryption; Asymmetric encryption: public and private pair key encryption, Digital Signatures, Virtual Private Network.

UNIT V: ELECTRONIC PAYMENTS Overview, The SET protocol, Payment Gateway, certificate, digital Tokens, Smart card, credit card, magnetic strip card, E-Checks, Credit/Debit card based EPS, online Banking.EDI Application in business, E- Commerce Law, Forms of Agreement, Govt. poli-cies and Agenda.

TEXT BOOKS

1. Ravi Kalakota, Andrew Winston, “Frontiers of Electronic Commerce”, Addison Wesley.

REFERENCE BOOKS

1. Pete Lohsin , John Vacca “Electronic Commerce”, New Age International 2. Goel, Ritendra “E-commerce”, New Age International 3. Laudon, “E-Commerce: Business, Technology, Society”, Pearson Education 4. Bajaj and Nag, “E-Commerce the cutting edge of Business”, TMH 5. Turban, “Electronic Commerce 2004: A Managerial Perspective”, Pearson Education

Software Engineering Learning Schedule L T P C

Pre-requisites: Basic Computing 3 0 0 3

COURSE DESCRIPTION This course is an introduction to software engineering process. Students are learned about software development process models and examine life cycle phases of software starting from: planning, problem analysis, requirements definition, specification, design, implementation, testing, maintenance and project management. The course also presents a collection of techniques for formal software development including operational, algebraic, model-based, property-based specification methods for the verification of consistency and completeness of specifications and for the verification of software properties. Students will be given approximately assignments and coursework in a group project. Team software development project using concepts and methodologies learned in software engineering classes and has to build a practical implementation of software development.


1. Design and develop software systems (including analysis, design, construction, maintenance, quality assurance and project management) using the appropriate theory, principles, tools and processes.

2. Use appropriate computer science and mathematics principles in the development of software systems.

3. Solve problems in a team environment through effective using various tools, techniques and processes.

4. Introduce the current issues presently involved in effectively performing duties as a software practitioner in an ethical and professional manner for the benefit of society.

5. Practice the lifelong learning needed in order to keep current as well as new challenging issues in real life scenario.

6. Develop software in at least one application domains like Healthcare, safety, Society, Legal, Environment, Communica-tion etc.


1. To apply software engineering theory, principles, tools and processes, as well as the theory and principles of computer sci-ence and mathematics, to the development and maintenance of complex software systems.

2. To design and validate various software prototypes and to develop quality software metrics. 3. To participate, productively in software project teams involving students from both software

engineering and other majors streams of computer scinec & engineering. 4. To design and develop standard procedures through oral and written reports and software

documentation evaluated by both peers and faculty. 5. To elicit, analyze and specify software requirements through a productive working relationship with

project stakeholders. 6. Analyze and implement application of network system.

COURSE CONTENT Unit I: Introduction to Software Engineering

Software Components, Software Characteristics, Software Crisis, Software Engineering Processes, Similarity and Differences from Conventional Engineering Processes, Software Quality Attributes. Software Development Life Cycle (SDLC) Models: Water Fall Model, Prototype Model, Spiral Model, Evolutionary Development Models, Iterative Enhancement Models. Unit II: Software Requirement Specifications (SRS)

Requirement Engineering Process: Elicitation, Analysis, Documentation, Review and Management of User Needs, Feasibility Study, Information Modeling, Data Flow Diagrams, Entity Relationship Diagrams, Decision Tables, SRS Document, IEEE Stan-dards for SRS. Software Quality Assurance (SQA): Verification and Validation, SQA Plans, Software Quality Frameworks, ISO 9000 Models, SEI-CMM Model. Unit III: Software Design Basic Concept of Software Design, Architectural Design, Low Level Design: Modularization, Design Structure Charts, Pseudo Codes, Flow Charts, Coupling and Cohesion Measures, Design Strategies: Function Oriented Design, Object Oriented Design, Top-Down and Bottom-Up Design. Software Measurement and Metrics: Various Size Oriented Measures: Halestead‟s Software Science, Function Point (FP) Based Measures, Cyclomatic Complexity Measures: Control Flow Graphs. Unit IV: Software Testing Testing Objectives, Module Testing, Integration Testing, Acceptance Testing, Regression Testing, Testing for Functionality and Testing for Performance, Top-Down and Bottom-Up Testing Strategies: Test Drivers and Test Stubs, Structural Testing (White Box Testing), Functional Testing (Black Box Testing), Test Data Suit Preparation, Alpha and Beta Testing of Products. Static Test-ing Strategies: Formal Technical Reviews (Peer Reviews), Walk Through, Code Inspection, Compliance with Design and Coding Standards. Unit V: Software Maintenance and Software Project Management Software as an Evolutionary Entity, Need for Maintenance, Categories of maintenance: Preventive, Corrective and Perfective Main-tenance, Cost of Maintenance, Software Re-Engineering, Reverse Engineering. Software Configuration Management Activities, Change Control Process, Software Version Control, an Overview of CASE Tools. Estimation of Various Parameters such as Cost, Efforts, Schedule/Duration, Constructive Cost Models (COCOMO), Resource Allocation Models, Software Risk Analysis and Management.

TEXT BOOKS

1. R. S. Pressman, Software Engineering: A Practitioners Approach, McGraw Hill. 2. K. K. Aggarwal and Yogesh Singh, Software Engineering, New Age International Publishers.

REFERENCE BOOKS 1. Rajib Mall, Fundamentals of Software Engineering, PHI Publication. 2. Pankaj Jalote, Software Engineering, Wiley 3. Carlo Ghezzi, M. Jarayeri, D. Manodrioli, Fundamentals of Software Engineering, PHI Publication. 4. Ian Sommerville, Software Engineering, Addison Wesley.

Soft computing Learning Schedule L T P C

Pre-requisites: C Programming 3 0 0 3

COURSE DESCRIPTION This course will provide students the basic concepts of different methods and tools for processing of uncertainty in intelligent systems, such as, fuzzy models, neural networks, probabilistic models, and foundations of its using in real systems. This course covers main concepts of philosophy of artificial intelligence, hybrid intelligent systems, classification and architecture of hybrid intelligent systems.

COURSE OBJECTIVES The objective of this course is to

1. familiarize with soft computing concepts 2. introduce and use the idea of Neural networks, fuzzy logic and use of heuristics based on human

experience 3. introduce and use the concepts of Genetic algorithm and its applications to soft computing using

some applications.


1. identify and describe soft computing techniques and their roles in building intelligent machines 2. recognize the feasibility of applying a soft computing methodology for a particular problem 3. apply fuzzy logic and reasoning to handle uncertainty and solve engineering problems, genetic

algorithms to combinatorial optimization problems and neural networks to pattern classification and regression problems

4. effectively use modern software tools to solve real problems using a soft computing approach and evaluate various soft computing approaches for a given problem.

COURSE CONTENT Unit I: Artificial Neural Networks

Basic-concepts-single layer perception-Multi layer perception-Supervised and unsupervised learning back propagation networks, Application. Unit II: Fuzzy Systems Fuzzy sets and Fuzzy reasoning-Fuzzy matrices-Fuzzy functions-decomposition-Fuzzy automata and languages- Fuzzy control methods-Fuzzy decision making, Applications. Unit III: Neuro-Fuzzy Modeling Adaptive networks based Fuzzy interfaces-Classification and Representation trees-Data dustemp algorithm – Rule base structure identification-Neuro-Fuzzy controls Unit IV: Genetic Algorithm Survival of the fittest-pictures computations-cross over mutation-reproduction-rank method-rank space method, Application. Unit V: Artificial Intelligence AI Search algorithm-Predicate calculus rules of interface - Semantic networks-frames-objects-Hybrid models, applications.

TEXT BOOKS

1. E - Neuro Fuzzy and Soft computing - Jang J.S.R., Sun C.T and Mizutami, Prentice hall New Jersey, 1998

2. Fuzzy Logic Engineering Applications - Timothy J.Ross, McGraw Hill, NewYork, 1997. 3. Fundamentals of Neural Networks - Laurene Fauseett, Prentice Hall India, New Delhi, 1994.

REFERENCE BOOKS 1. Introduction to Artificial Intelligence - E Charniak and D McDermott, Pearson Education 2. Artificial Intelligence and Expert Systems - Dan W. Patterson, Prentice Hall of India.

TCS420 Data Compression Learning Schedule

L T P C Pre-requisites: OS 3 0 0 3

COURSE DESCRIPTION The course covers the theory of quantization and basic concepts in source coding and applications of the theory and concepts to systems that convert analog or high-rate digital signals into low-rate digital representations with or without loss of fidelity. The con-cept of source coding is extended to general descriptions of a statistical information source where various data modeling techniques find useful applications.


4. gain a fundamental understanding of data compression methods for text, images, and video, and related issues in the storage, access, and use of large data sets

5. select, giving reasons that are sensitive to the specific application and particular circumstance, most appropriate compression techniques for text, audio, image and video information

6. illustrate the concept of various algorithms for compressing text, audio, image and video information.


1. program, analyze Hoffman coding: Loss less image compression, Text compression, Audio Compression

2. program and analyze various Image compression and dictionary based techniques like static Dictionary, Diagram Coding, Adaptive Dictionary

3. understand the statistical basis and performance metrics for lossless compression 4. understand the conceptual basis for commonly used lossless compression techniques, and understand

how to use and evaluate several readily available implementations of those techniques 5. understand the structural basis for and performance metrics for commonly used lossy compression

techniques and conceptual basis for commonly used lossy compression techniques.

COURSE CONTENT Unit I: Compression Techniques

Loss less compression, Lossy Compression, Measures of performance, Modeling and coding, Mathematical Preliminaries for Loss-less compression: A brief introduction to information theory, Models: Physical models, Probability models, Markov models, com-posite source model, Coding: uniquely decodable codes, Prefix codes. Unit II: The Huffman coding algorithm Minimum variance Huffman codes, Adaptive Huffman coding: Update procedure, Encoding procedure, Decoding procedure. Golomb codes, Rice codes, Tunstall codes, Applications of Hoffman coding: Loss less image compression, Text compression, Audio Compression. Unit III: Coding Coding a sequence, Generating a binary code, Comparison of Binary and Huffman coding, Applications: Bi- level image compression- The JBIG standard, JBIG2, Image compression. Dictionary Techniques: Introduction, Static Dictionary: Diagram Coding, Adaptive Dictionary. The LZ77 Approach, The LZ78 Approach, Applications: File Compression-UNIX compress, Image Compression: The Graphics Interchange Format (GIF), Compression over Modems: V.42 bits, Predictive Coding: Prediction with Partial match (ppm): The basic algorithm, The ESCAPE SYMBOL, length of context, The Exclusion Principle, The Burrows-Wheeler Transform: Move to- front coding, CALIC, JPEG-LS, Multi-resolution Approaches, Facsimile Encoding, Dynamic Markoy Compression. Unit IV: Scalar Quantization Distortion criteria, Models, Scalar Quantization: The Quantization problem, Uniform Quantizer, Adaptive Quantization, Non uniform Quantization.

Unit V: Vector Quantization Advantages of Vector Quantization over Scalar Quantization, The Linde-Buzo-Gray Algorithm.

TEXT BOOKS

1. The Data Compression Book - Mark Nelson. 2. Data Compression: The Complete Reference - David Salomon.

REFERENCE BOOKS

3. Introduction to Data Compression - Khalid Sayood, Morgan Kaufmann Publishers.

Computer Networks Lab Learning Schedule L T P C

Pre-requisites: Internet Fundamental 0 0 2 1

COURSE OBJECTIVES

The objective of this course is to:

1. Familiarize students with different Networks components such as switch, routers etc. 2. Make them comfortable in socket programming and internet programming.

COURSE OUTCOMES

At the end of course the student will be able to:

1. Understand basic Network Commands. 2. Understand the basic functioning of Switches and routers etc. 3. Understand functioning of different layers. 4. Write program for client and server using socket programming.

LIST OF EXPERIMENTS:

1. Introduction to basic Linux networking commands. (Commands like ipconfig, getmac, tracert, pathping, arp, ping, netstat, finger etc.)

2. Implement bit stuffing and de-stuffing 3. Write a program for hamming code generation for error detection and correction. 4. Implement cyclic redundancy check (CRC). 5. Write a program for congestion control using the leaky bucket algorithm. 6. Implement Dijkstra‟s algorithm to compute a shortest path through graph. 7. Take a 64-bit plain text and encrypt the same using DES algorithm. 8. Using RSA algorithm encrypts a text data and decrypts the same. 9. Implementation of the link state routing protocols. 10. Implementation of LZW compression and decompression algorithms.

Software Engineering Lab Learning Schedule L T P C

Pre-requisites: Programming 0 0 2 1

COURSE OBJECTIVES:


1. Design and implement software solutions that accommodate specified requirements and constraints,

based on analysis or modeling or requirements specification. 2. Analyze and model requirements and constraints for the purpose of designing and implementing

software systems; 3. Evaluate and compare designs of such systems on the basis of requirements of the organizational

needs. COURSE OUTCOMES At the end of the course student will be able to:

1. Apply knowledge of UML, source control, and project management. 2. Implementing their project and work with end user. 3. Test and document software. 4. Work as part of a software team and develop significant projects under a tight deadline. 5. Present their work in a professional manner. 6. Design and implement complex software solutions using state of the art software engineering

techniques. LIST OF EXPERIMENTS:

1. Model your system design using either refined Object Diagrams or Structure Charts depending on

whether you are using the Object-Oriented or Function-Oriented approach respectively (ER, Use- Case Class Diagram).

2. As you model, you may need to update or refine your earlier assumptions and requirements. It would be expedient if you as-sign a team member to update/refine your preliminary system specification obtained in Experiment 1 while the system design is being worked out by other members‟ assigned designer roles.

3. How to keep a copy of your system design (one copy is sufficient for each project team). For consistency during implementa-tion, all members should reference the same version of the system design.

4. Install RSA software development tool and familiarize yourself with it. 5. In the course of the current lab session, you may need to update/refine your preliminary system

specification and make changes to your project schedule and/or team organization structure. 6. The manpower allocation information in your project schedule. Assign implementation work

accordingly and equitably. You may need to reassign roles, e.g. have more programmers, if you are behind schedule though network diagram and indicate properly critical task.

7. Create, compile, link and test your assigned objects or modules. 8. Complete project schedule using Gantt Chart. 9. For small size and complexity of your projects, desk checking and compiling are the best form of

static testing (Alpha Test). Alternatively, if you are ahead of schedule and perhaps just for the experience, you may wish to conduct a mock-up of a walk-through or inspection involving your team members and a selected sub-system component.

10. Perform dynamic testing (Beta Testing). 11. Perform white box testing on individual software components while aggregates (clusters) of software

components should progressively be subjected to black box testing. Perform regression tests for completeness, as your aggregates get incrementally larger.

12. Make realistic approach of unit testing and integration strategy.

Industrial Exposure -II Learning Schedule L T P C

Pre-requisites: Basic knowledge of Computers 0 0 0 1

COURSE OBJECTIVES:

1. To gain industrial exposure through industrial visit in core companies. 2. To experience the discipline of working in a professional organisation and multidisciplinary

team. 3. To develop interpersonal, technical and communication skills.

COURSE OUTCOMES


1. Get exposure to real-life-working environment & practices, and to attain the professionalisms. 2. Work with multi-tasking professionals and multidisciplinary team. 3. To aware about portfolio of industry.

COURSE CONTENT Industrial visit / Industrial Tour in various organisation related to respective discipline.

Campus To Corporate Learning Schedule L T P C

Pre-requisites: Adaptive 0 0 4 2

COURSE OBJECTIVES:

1. To make the students aware of some more techniques of Presentation. 2. To make them practice the interview questions (Moke interviews) COURSE OUTCOMES:

1. Students are confident to give independent presentations professionally. 2. Prepare for the interviews. COURSE CONTENT

Unit-I Presentation Strategies:

Defining purpose, audience and locale, organizing content, Preparing outlines ,audio visual aids ,nuances of body language ,space, setting nuances and voice dynamics, build confidence, handling questions, collocations to be used for day to day conversation, improve the ability to present in front of the group Unit-II: Situation Based Conversation Conversations in Pairs to be Conducted (based on situations related to day-today life), Enhancing communication Skills through Situation Based Conversations. Unit-III: Professional Skills Meetings, Agenda, Minutes of the Meeting, Business Etiquette. Unit-IV Group Discussions and Role Play Personality Traits to be evaluated, Dynamics of Group Behavior, Group Etiquettes and Mannerism, Tips for Effective Group Discussion, Situation Based Role Play in Groups, Unit-V: Mock Interviews Practice through Mock Interviews for Recruitment.

TEXT BOOKS:

1. E. Suresh Kumar, P. Sreehari and J. Savithri „Communication Skills and Soft Skills An Integrated Approach‟, Pearson 2012

2. Nitin Bhatnagar and Mamta Bhatnagar „Effective Communication and Soft Skills: Strategies for Success‟, Pearson 2012

3. Francis Peter S. J „Soft Skills and Professional Communication‟, Tata McGraw-Hill 2012. REFERENCE BOOKS:

1. Barun K. Mitra „Personality Development and Soft Skills‟, Oxford University Press 2011 2. Dr. Seema Miglani, Shikha Goyal and Rohit Phutela „Communication Skills-II‟, Vayu Education of

India 2009 3. L. Ann Masters and Harold R. Wallace „Personal Development for life and Work‟ Cengage Learning

2012

Technical Skills for Computer Engineers-IV Learning Schedule

L T P C

Pre-requisites: Programming Language 0 0 2 1

COURSE OBJECTIVES 1. use Python interactively 2. execute a Python script at the shell prompt 3. use Python types, expressions, and None 4. use string literals and string type 5. use Python statements (if...elif..else, for, pass, continue, . . . ) 6. understand the difference between expressions and statements 7. understand assignment semantics 8. write and call a simple function 9. utilize high-level data types such as lists and dictionaries 10. understand the difference between mutable and immutable types 11. write a simple class and access methods and attributes 12. import and utilize a module • read from and write to a text file 13. understand interpreter and compilers: CPython, PyPy, Cython 14. see demonstration of IDE‟s: IDLE, IPython, IPython Notebook, hosted environments 15. understand the role of package managers: easy_install, pip 16. understand what NumPy does and what SciPy is (are?) 17. learn about resources for learning Python3

COURSE OBJECTIVES Python is a popular, general-purpose, multi-paradigm, open-source, scripting language. It is designed to emphasize code readability – has a clean syntax with high level data types. It is the need of B.Tech Students and helpful to build a career. COURSE CONTENT Unit I: Introduction to Python. An introduction to the Python programming language. Covers details of how to start and stop the interpreter and write programs. Introduces Python's basic datatypes, files, functions, and error handling. Working with Data. A detailed tour of how to represent and work with data in Python. Covers tuples, lists, dictionaries, and sets. Students will also learn how to effectively use Python's very powerful list processing primitives such as list comprehensions. Finally, this section covers critical aspects of Python's underlying object model including variables, reference counting, copying, and type checking. Unit- II : Program Organization and Functions. More information about how to organize larger programs into functions. A major focus of this section is on how to design functions that are reliable and can be easily reused in other settings. Also covers technical details of functions including scoping rules and documentation strings. Modules and Libraries. How to organize programs into modules and details on using modules as a tool for creating extensible programs. Concludes with a tour of some of the most commonly used library modules including those related to system administration, text processing, subprocesses, XML parsing, binary data handling, and databases. Also includes information on how to install third-party library modules. Unit III : Classes and Objects. An introduction to object-oriented programming in Python. Describes how to create new objects, overload operators, and utilize Python special methods. Also covers basic principles of object oriented programming including inheritance and composition. Inside the Python Object System. A detailed look at how objects are implemented in Python. Major topics include object representation, attribute binding, inheritance, memory management, and special properties of classes including properties, slots, and private attributes. Unit IV : Testing, Debugging, and Software Development Practice. This section discusses many isses that are considered important to Python software development. This includes effective use of documentation

strings, program testing using both the doctest and unittest modules, and effective use of assertions. The Python debugger and profiler are also described. Iterators and Generators. Covers the iteration protocol, iterable objects, generators and generator expressions. A major focus of this section concerns the use of generators to set up data processing pipelines- -a particularly effective technique for addressing a wide variety of common systems programming problems (e.g., processing large datafiles, handling infinite data streams, etc.). Text I/O Handling. More information on text-based I/O. Topics include text generation, template strings, and Unicode. Some Advanced Topics. A variety of more advanced programming topics including variable argument functions, anonymous functions (lambda), closures, decorators, static and class methods, and packages. Python Integration Primer. A survey of how Python is able to interact with programs written in other programming languages. Topics include network programming, accessing C code, COM extensions, Jython, and IronPython.

TEXT BOOKS

1. Learning to Program Using Python by Cody Jackson 2. Python for complete beginners by Dr. Martin Jones

REFERENCE BOOKS

1. Fundamentals of Python: First Programs by Ken Lambert 2. Learning Python, 5th Edition by Mark Lutz, O'Reilly Media. 3. Easy GUI Programming in Python by Ken Lambert 4. The Practice of Computing Using Python by Bill Punch and Rich Enbody

https://www.createspace.com/3611970

http://www.amazon.com/Python-complete-beginners-friendly-experience/dp/1514376989/

http://www.cengagebrain.com/shop/isbn/9781111822705

http://home.wlu.edu/%7Elambertk/breezypythongui/easyguibook.html

http://www.pearsonhighered.com/educator/product/Practice-of-Computing-using-Python-The/9780136110675.page

Industrial Economics and Management Learning Schedule L T P C


COURSE DESCRIPTION: The course describes the basics of demand and demand forecasting. It explains cost functions, cost control, cost reduction and pricing techniques.

EXPECTED OUTCOME: On completion of this course, the students will be able to 1. Apply the concept of demand. 2. Estimate production and cost function. 3. Formulate appropriate pricing strategies.

Unit I Introduction Introduction: The Scope and Method of Managerial economics – Fundamental Economics concepts – Managerial Economics with other subjects - Objectives of the Firm

Unit II Demand and Supply Analysis Meaning, Types and Determinants – Demand estimation- Demand elasticities for decision making – Business and Economic forecasting: Qualitative and Quantitative methods – Supply analysis: Meaning, elasticities and determinants – Market equilibrium and price determination

Unit III Production Economics Production and Production function – Types – Estimation – Returns to Scale – Economies and Diseconomies of Scale and Economies of Scope. Factor Inputs - Input-Output Analysis

Unit IV Market Structure Perfect Competition – Imperfect Competition: Monopoly – Monopolistic – Oligopolistic Strategy, Cartels, Cournot, Kinked Demand and Price Leadership. Oligopolistic Rivalry & Theory of Games – Measurement of economic concentration – Policy against monopoly and restrictive trade practices - Competition Law – Pricing Practices: Objectives – Determinants – Pricing Methods – Government Policies and Pricing.

Unit V Introduction to Macroeconomics Circular Flow of Income and Expenditures – Components of National Income and its significance - Measuring Gross Domestic Product (GDP) – Inflation and Business Cycles – Government Fiscal and Monetary Policy - Balance of payments – Foreign exchange markets

TEXT BOOKS 1. P.L. Mehta – Managerial Economics Analysis, Problems and cases, Sultan Chand & Co. Ltd., 2001

REFERENCES: 1. Peterson and Lewis: Managerial Economics, 4th Ed., Prentice Hall , 2004 2. Dholakia and Oza: Microeconomics for Management Students, 2nd Edition, Oxford University Press 3. Gregory Mankiw: Principles of Microeconomics, Havcourt Asia Publishers, 2001 4. Mote and paul – Managerial Economics, Tata McGraw Hill, 2001

Probability and Statistics Learning Schedule

L T P C Pre-requisites: Basic Mathematics 3 0 0 3

COURSE OBJECTIVES :

1. To give an exposure to the students the basic concepts of Probability and Statistical methods and their application.

2. To serve as a foundation to analyze problems in Science and Engineering applications through Statistical testing Method.

COURSE OUTCOMES : On completion of this course, the students are expected to learn Basics of Probability distributions, Sampling theory and Theory of Estimation Various tests of Hypothesis and Significance, Correlation and Regression and fitting of different types of curves . COURSE CONTENT : Unit I: Probability Distributions

Review of basic probability, Random variables, Probability Distribution, Mathematical Expectation and Variance of Probability distribution, Standard discrete distributions: Binomial, Poisson and Geometric distributions, Probability density function, Cumu-lative distribution function, Expectation and Variance, Standard continuous distributions - Uniform, Normal, Exponential, Joint distribution and Joint density functions Unit II: Sampling Theory Population and Sample, Statistical inference, Sampling with and without replacement, Random samples, Population parameters, Sample statics, Sampling distributions, Sample mean, Sampling distribution of means, Sample variances, Sampling distribution of variances, Case where population variances is unknown, Unbiased estimates and efficient estimates, point estimate and Interval Estimates, Confidence Interval estimates of population parameters, Confidence intervals for variance of a Normal distribution, Maximum likelihood estimates. Unit III: Tests of Hypothesis and Significance Statistical hypothesis, Null and Alternate hypothesis, test of hypothesis and significance, Type I and Type II errors, Level of Sig-nificance, Tests involving the Normal distribution, One-Tailed and Two-Tailed tests, P value. Special tests of significance for Large samples and Small samples (F, chi- square, z, t- test), ANOVA. Unit IV: Correlation and Regression Correlation, Rank correlation, Regression Analysis, Linear and Non linear Regression, Multiple regression, Curve fitting by meth-od of least squares, fitting of straight lines, polynomials, exponential curves.

TEXT BOOKS:

1. R. E. Walpole, R. H. Mayers, S. L. Mayers and K. Ye, (2007), Probability and Statistics for Engineers and Scientists,8th Edition, Pearson Education, ISBN: 978-8-131-71552-9.

2. Sheldon M. Ross, (2011), Introduction to Probability and Statistics for Engineers and Scientists, 4th Edition, Academic Foundation, ISBN: 978-8-190-93568-5.

REFERENCE BOOKS:

1. Douglas C. Montgomery, (2012), Applied Statistics and Probability for Engineers, 5th Edition, , Wiley India, ISBN: 978-8-126-53719-8.

2. Spiegel, M. R., Schiller, J. and Srinivasan, R. A., (2010), Probability & Statistics, 3rdEdition, TataMcGraw Hill, ISBN : 978-0-070-15154-3.

Theory of Automata & Formal Language Learning Schedule L T P C

Pre-requisites: ADA 3 1 0 4

COURSE DESCRIPTION This course introduces some fundamental concepts in automata theory and formal languages including grammar, finite automaton, regular expression, formal language, pushdown automaton and Turing machine. This subject not only forms the basic models of computation, it also includes the foundation of many branches of computer science, e.g. compilers, software engineering, concurrent systems, etc. The properties of these models will be studied and various rigorous techniques for analysing and comparing them will be discussed, by using both formalism and examples.

COURSE OBJECTIVES 3. introduce the student to the concepts of theory of computation in computer science. 4. acquire insights into the relationship among formal languages, formal grammars, and automata. 5. learn to design automats and Turing machine

COURSE OUTCOMES 4. demonstrate an understanding of abstract models of computing, including deterministic (DFA), non-

deterministic (NFA), and Turing (TM) machine models. 5. demonstrate an understanding of regular expressions and grammars, including context-free and

context-sensitive gram-mars. 6. understand the relationships between language classes, including regular, context-free, context-

sensitive, recursive, and recursively enumerable languages. 7. able to design Turing Machine


Alphabets, Strings and Languages; Automata and Grammars, Deterministic finite Automata (DFA)-Formal Definition, Simplified notation: State transition graph, Transition table, Language of DFA, Nondeterministic finite Automata (NFA), NFA with epsilon transit ion, Language of NFA, Equivalence of NFA and DFA, Minimization of Finite Automata, Distinguishing one string from other, Myhill-Nerode Theorem. Unit II: Regular expression (RE) Regular expression (RE) Definition, Operators of regular expression and their precedence, Algebraic laws for Regular expressions, Kleen‟s Theorem, Regular expression to FA, DFA to 39 Regular expression, Arden Theorem, Non Regular Languages, Pumping Lemma for regular Languages . Application of Pumping Lemma, Closure properties of Regular Languages, Decision properties of Regular Languages, FA with output: Moore and Mealy machine, Equivalence of Moore and Mealy Machine, Applications and Limitation of FA. Unit III: Context free grammar (CFG) & Context Free Languages CFL) Definition, Examples, Derivation, Derivation trees, Ambiguity in Grammer, Inherent ambiguity, Ambiguous to Unambiguous CFG, Useless symbols, Simplification of CFGs, Normal forms for CFGs: CNF and GNF, Closure proper ties of CFLs, Decision Properties of CFLs: Emptiness, Finiteness and Membership, Pumping lemma for CFLs. Unit IV: Push Down Automata (PDA) Description and definition, Instantaneous Description, Language of PDA, Acceptance by Final state, Acceptance by empty stack, Deterministic PDA, Equivalence of PDA and CFG, CFG to PDA and PDA to CFG, Two stack PDA. Unit V: Turing machines (TM) Basic model, definition and representation, Instantaneous Description, Language acceptance by TM, Variants of Turing Machine, TM as Computer of Integer functions, Universal TM, Church‟s Thesis, Recursive and recursively enumerable languages, Halting problem, Introduction to Undecidability, Undecidable problems about TMs. Post correspondence problem (PCP), Modified PCP, Introduction to recursive function theory.

TEXT BOOKS 1. Theory of Computer Science : Automata, Languages and Computation - K.L.P. Mishra and

N.Chandrasekaran,”, PHI 2. Introduction to Languages and Theory of Computations - Martin J. C., TMH

REFERENCE BOOKS

1. Introduction to Automata Theory, Languages and Computation - Hopcroft, Ullman, Pearson Education

2. Elements of the Theory of Computation - Papadimitrou, C. and Lewis, C.L, PHI

Software Development & Testing Methodology Learning Schedule L T P C

Pre-requisites: Software Engineering 3 0 0 3

COURSE DESCRIPTION This course will examine fundamental software testing and program analysis techniques. In particular, the important phases of testing will be reviewed, emphasizing the significance of each phase when testing different types of software. Students will learn the state of the art in testing technology for object-oriented, component-based, concurrent, distributed, graphical-user interface, and web software. In addition, closely related concepts such as mutation testing and program analysis (e.g., program-flow and data-flow analysis) will also be studied. Emerging concepts such as test-case prioritization and their impact on testing will be examined. Stu-dents will gain hands-on testing/analysis experience via a multi-phase course project. By the end of this course, students should be familiar with the state-of-the-art in software testing. Students should also be aware of the major open research problems in testing.

COURSE OBJECTIVES The objective of this course is:

1. Introducing various design approaches, models and metrics. 2. Presenting various techniques and strategies of software testing and inspection and pointing out the

importance of testing in achieving high-quality software. 3. Understand concept of reliability, the role it plays in software engineering, and how it is modeled and

measured. 4. Showing how software product and process are managed and controlled for maintaining software

quality assurance. 5. Highlighting importance of software maintenance, restructuring, and reengineering. 6. Presenting the various techniques of software cost estimation and risk assessment.


1. Use the appropriate methods and tools for estimating software cost. 2. Understand the difference between different software design models and techniques and how to

apply them. 3. Recognize the importance of software reliability and how we can design dependable software, and

what measures are used. 4. Understand the principles and techniques underlying the process of inspecting and testing software

and making it free of errors and tolerable. 5. Recognize the importance of software standards and quality assurance. 6. Apply the appropriate software evolution methods for maintaining, restructuring available software

and managing soft-ware development. COURSE CONTENT

Unit I: Introduction

Faults, Errors, and Failures, Basics of software testing, Testing objectives, Principles of testing, Requirements, behavior and cor-rectness, Testing and debugging, Test metrics and measurements, Verification, Validation and Testing, Types of testing, Software Quality and Reliability, Software defect tracking. Unit II: White Box and Black Box Testing White box testing, static testing, static analysis tools, Structural testing: Module/Code functional testing, Code coverage testing, Code complexity testing, Black Box testing, Requirements based testing, Boundary value analysis, Equivalence partitioning, state/ graph based testing, Model based testing and model checking, Differences between white box and Black box testing. Unit III: Integration, System, and Acceptance Testing

Top down and Bottom up integration, Bi-directional integration, System integration, Scenario Testing, Defect Bash, Functional versus Non-functional testing, Design/Architecture verification, Deployment testing, Beta testing, Scalability testing, Reliability testing, Stress testing, Acceptance testing: Acceptance criteria, test cases selection and execution, Unit IV: Test Selection & Minimization for Regression Testing Regression testing, Regression test process, Initial Smoke or Sanity test, Selection of regression tests, Execution Trace, Dynamic Slicing, Test Minimization, Tools for regression testing, Ad hoc Testing: Pair testing, Exploratory testing, Iterative testing, Defect seeding. Unit V: Test Management and Automation Test Planning, Management, Execution and Reporting, Software Test Automation: Scope of automation, Design & Architecture for automation, Generic requirements for test tool framework, Test tool selection, Testing in Object Oriented Systems. TEXT BOOKS

1. S. Desikan and G. Ramesh, “Software Testing: Principles and Practices”, Pearson Education.

REFERENCE BOOKS 1. Aditya P. Mathur, “Fundamentals of Software Testing”, Pearson Education. 2. Naik and Tripathy, “Software Testing and Quality Assurance”, Wiley 3. K. K. Aggarwal and Yogesh Singh, “Software Engineering”, New Age International Publication.

Advanced Java Learning Schedule L T P C

Pre-requisites: C++ 3 0 0 3

COURSE DESCRIPTION A major focus of this course is the technology and the drive towards web services and e-business. To achieve this, student has to understand about the core topics of java and advanced java. The course basically deals with the concepts of java through which a desktop application as well as a static or dynamic web can be developed.

COURSE OBJECTIVES


1. Introduce Java as a programming language. 2. Introduce Java as a dynamic web programming language. 3. Develop applications using Java. 4. Introduce the concepts of JDBC for the purpose of database connectivity. 5. Describe the technique to develop networking or socket programming.

COURSE OUTCOMES

At the end of the course student will be able to:

1. Design a desktop application which can used for many kind of clients. 2. Design a web application which can work as a dynamic web with the help of JDBC. 3. Develop an application which can also be connected with the database.

COURSE CONTENT

Unit I: CORE JAVA

Introduction to Java, Data types, variables, operators, Arrays, Control Statements, Classes & Methods, Inheritance, Exception Handling, Multithreading, Collections, I/O streams. Unit II: NETWORKING Connecting to a Server, Implementing Servers, Sending E-Mail, Making URL Connections, Advanced Socket Programming DATABASE NETWORKING: The Design of JDBC. The Structured Query Language, JDBC Installation, Basic JDBC Programming Concepts, Query Execution, Scrollable and Updatable Result Sets, Metadata, Row Sets, Transactions. Unit III: AWT and SWING Lists, Trees, Tables, Styled Text Components, Progress Indicators, Component Organizers The Rendering Pipeline, Shapes, Areas, Strokes, Paint, Coordinate Transformations, Clipping, Transparency and Composition, Rendering Hints, Readers and Writers for Images, Image Manipulation, Printing. The Clipboard, Drag and Drop. Unit IV: JAVABEANS COMPONENTS Beans, The Bean-Writing Process, Using Beans to Build an Application, Naming Patterns for Bean, Components and Events Bean Property, Tubes Bean info Classes, Property, Editors, Customizes. Unit V: JSP and SERVLETS Introduction to JSP, JSP built in objects, tags, Servlets, mapping, a web application.

TEXT BOOKS

1. Core JavaTM 2, Volume II-Advanced Features, 7th Edition by Cay Horetmann,Gary Cornelll Pearson Publisher, 2004

REFERENCE BOOKS

1. Professional Java Programming by Brett Spell, WROX Publication 2. Advanced Java 2 Platform, How to Program, 2nd Edition, Harvey. M. Dietal, Prentice Hall. 3. Advanced Java, Gajendra Gupta , Firewall Media.

Distributed System Learning Schedule L T P C

Pre-requisites: DWDM 3 0 0 3

COURSE DESCRIPTION This course covers a broad range of topics related to parallel and distributed computing, including parallel and distributed archi-tectures and systems, parallel and distributed programming paradigms, parallel algorithms and scientific and other applications of parallel and distributed computing.


1. Familiarize the students with the basics of distributed computing systems. 2. To introduce the concepts of distributed file systems, shared memory and message passing systems,

synchronization and resource management.


1. Verify and analyze the time complexity of the algorithms related to distributed computing. 2. Design and develop various algorithms for problems in distributed computing 3. Compare various resource allocation stratagies.

COURSE CONTENT

Unit I: INTRODUCTION

Definition - Evolution- Goals of distributed systems, system models- Issues in the design of distributed systems- Distributed com-puting environment. Unit II: COMMUNICATION Message Passing – Features and Issues -Synchronization-Buffering - Process Addressing - Failure Handling - Remote procedure call (RPC): Model – Implementation - Stub generation - RPC messages – Marshaling - server Management - Call semantics - communication protocols for RPC-Client server binding – RMI. Unit III: DISTRIBUTED SHARED MEMORY Distributed shared memory- Design and implementation issues- Sequential consistency - Release consistency, Process migration Features & Mechanism Unit IV: SYNCHRONIZATION Synchronizing physical clocks - Logical clocks - Distributed coordination – Event Ordering – Mutual Exclusion – Deadlock - Elec-tion algorithms. Unit V: DISTRIBUTED FILE SYSTEMS Introduction – File Models – File accessing, sharing and caching - File Replication – Atomic transactions Case Study HADOOP. : Resource and process management - Task assignment approach - Load balancing approach - Load sharing approach TEXT BOOKS

1. George Colouris, Jean Dollimore and Tim Kindberg, “Distributed Systems – Concepts and Design”, Pearson Education Private Limited, New Delhi, 2001

2. Pradeep K Sinha, “Distributed Operating Systems: Concepts and Design”, Prentice Hall of India, New Delhi, 2003.

REFERENCE BOOKS

1. Gerard Tel, “Introduction to Distributed algorithms”, Cambridge University Press, USA, 2000. 2. Andrzej Goscinski, “Distributed Operating Systems, the logical Design”, Addison

Wesley Publishing Company, USA, 1991. 3. Tanenbaum, “Modern Operating Systems”, Prentice Hall of India, New Delhi, 1999. 4. Patrick Naughton and Herbert Schildt, “Java 2- The Complete Reference”, Tata McGraw Hill, New

Delhi, 2007.

. Wireless and Mobile Communication Learning Schedule

L T P C Pre-requisites: Computer Networks 3 0 0 3

COURSE DESCRIPTION In this course, students examine fundamental concepts of mobile cellular communications and specifics of current and proposed U.S. cellular systems. Topics include frequency reuse, call processing, propagation loss, multipath fading and methods of reducing fades, error correction requirements and techniques, modulation methods: FDMA, TDMA, and CDMA techniques, microcell issues, mobile satellite systems and IMT-2000 COURSE OBJECTIVES The objective of this course is to:

1. Introduce of wireless communication and mobile communication standards. 2. Provide understanding of advanced multiple access techniques, Mobile radio Propagation Models

and modulation tech-niques 3. Provide understanding of digital cellular systems (GSM, CDMA, GPRS, W-CDMA etc.)


1. Understand principles of wireless communication and, various mobile network architecture. 2. Understand various Modulation techniques for Mobile Radio. 3. Understand the information theoretical aspects (such as the capacity) of wireless channels 4. Realize various wireless and mobile cellular communication systems 5. Implement practical mobile applications

COURSE CONTENT UNIT I: INTRODUCTION TO WIRELESS COMMUNICATIONS

History and evolution of mobile radio systems. Types of mobile wireless services/systems-Cellular, WLL, Paging, Satellite systems, Standards, Future trends in personal wireless systems. UNIT II: CELLULAR CONCEPTS AND SYSTEM DESIGN FUNDAMENTALS Cellular concept and frequency reuse, Multiple Access Schemes, channel assignment and handoff, Interference and system capacity, Trunking and Erlang capacity calculations. UNIT III: MOBILE RADIO PROPAGATION MODELS Radio wave propagation issues in personal wireless systems, Propagation models, Multipath fading and Base band impulse respond models, parameters of mobile multipath channels, Antenna systems in mobile radio. UNIT IV: MODULATION TECHNIQUES Overview analog and digital modulation techniques, Performance of various modulation techniques-Spectral efficiency, Error-rate, Power Amplification, Equalizing Rake receiver concepts, Diversity and space-time processing, Speech coding and channel coding. UNIT V: SYSTEM EXAMPLES AND DESIGN ISSUES Multiple Access Techniques-FDMA, TDMA and CDMA systems, operational systems, Wireless networking, design issues in per-sonal wireless systems TEXT BOOKS

1. T. S. Rappaport, Wireless digital communications; Principles and practice, Prentice Hall, NJ, 1996. 2. Schiller, Mobile Communications; Pearson Education Asia Ltd., 2000.

REFERENCE BOOKS

1. K. Feher, Wireless digital communications, PHI, New Delhi, 1999. 2. W. C. Y. Lee, Mobile communications engineering: Theory and Applications, Second Edition,

McGraw Hill, New York.1998.

Enterprise Resource Planning Learning Schedule L T P C

Pre-requisites: E-Business 3 0 0 3

COURSE DESCRIPTION This course serves as an introduction to the world of Enterprise Resource Planning and also provides foundation for many disci-plines in common business modern information systems. By studying both successful and unsuccessful implementation of En-terprise Resource Planning software, students will examine how and why an ERP system is implemented and how it is integrated with existing business processes. Students will get to know what the impact of ERP on the organization is and how change can be managed. For demonstration an ERP system such as SAP will be used to experience several business processes. COURSE OBJECTIVES The objective of this course is to:

1. Describe the concept of ERP and the ERP model; define key terms; explain the transition from MRP to ERP; identify the levels of ERP maturity.

2. Explain how ERP is used to integrate business processes; define and analyze a process; create a process map and improve and/or simplify the process; apply the result to an ERP implementation.

3. Describe the elements of a value chain, and explain how core processes relate; identify how the organizational infrastruc-ture supports core business processes; explain the effect of a new product launch on the three core business processes.


1. Develop model for ERP for large projects 2. Develop model for E-commerce architecture for any application 3. Describe the advantages, strategic value, and organizational impact of utilizing an ERP system for

the management of information across the functional areas of a business: sales and marketing, accounting and finance, human resource man-agement, and supply chain.

4. Demonstrate a working knowledge of how data and transactions are integrated in an ERP system to manage the sales order process, production process, and procurement process.

5. Evaluate organizational opportunities and challenges in the design system within a business scenario. COURSE CONTENT

Unit I

ERP Introduction, Benefits, Origin, Evolution and Structure: Conceptual Model of ERP, the Evolution of ERP, the Structure of ERP. Unit II Business Process Reengineering, Data ware Housing, Data Mining, Online Analytic Processing (OLAP), Product Life Cycle Man-agement (PLM), LAP, Supply chain Management. Unit III ERP Marketplace and Marketplace Dynamics: Market Overview, Marketplace Dynamics, the Changing ERP Market. ERP- Func-tional Modules: Introduction, Functional Modules of ERP Software, Integration of ERP, Supply chain and Customer Relationship Applications. Unit IV ERP Implementation Basics, ERP Implementation Life Cycle, Role of SDLC/SSAD, Object Oriented Architecture, Consultants, Vendors and Employees. Unit V ERP & E-Commerce, Future Directives- in ERP, ERP and Internet, Critical success and failure factors, Integrating ERP into or-ganizational culture. Using ERP tool: either SAP or ORACLE format to case study.

TEXT BOOKS

1. Vinod Kumar Garg and Venkitakrishnan N K, “Enterprise Resource Planning Concepts and Practice”, PHI.

2. Joseph A Brady, Ellen F Monk, Bret Wagner, “Concepts in Enterprise Resource Planning”, Thompson Course Technology.

REFERENCE BOOKS

1. Alexis Leon, “ERP Demystified”, Tata McGraw Hill 2. Rahul V. Altekar “Enterprise Resource Planning”, Tata McGraw Hill, 3. Vinod Kumar Garg and Venkitakrishnan N K, “Enterprise Resource Planning – A Concepts and

Practice”, PHI 4. Mary Summer, “Enterprise Resource Planning”- Pearson Education

Advanced Java Lab Learning Schedule L T P C


COURSE OBJECTIVES:


4. Design and implement concepts of java to develop desktop application 5. Design and implement concepts of java to develop web application.

COURSE OUTCOMES


7. Apply basics of java to prepare a console based application. 8. Apply core concepts of java to develop desktop application. 9. Design a web application by the jsp and servlets.

LIST OF EXPERIMENTS:

1. Create a program in java to sort an array using java. 2. Create a program in java to read data from the user through I/O streams. 3. Create a program in java to handle exceptions. 4. Create a program to in java to implement threads. 5. Create a program in java to transfer data of a file to another file. 6. Create a desktop application using AWT and SWING. 7. Create a desktop application which uses JDBC 8. Create a static web using java concepts. 9. Create a dynamic web using java concepts. 10. Create a dynamic web using JSP,Servlets,JDBC.

Industrial Training -II Learning Schedule L T P C

Pre-requisites: Programming Language - - - 2

COURSE OBJECTIVES:

7. To gain experience of working as an engineering professional,including the technical application of engineering knowledge.

8. To experience the discipline of working in a professional organisation and multidisciplinary team. 9. To develop technical, interpersonal and communication skills.

COURSE OUTCOMES


9. Apply engineering knowledge in solving real-life problems. 10. Attain new skills and be aware of the state-of-art in engineering disciplines of their own interest. 11. Get exposure to real-life-working environment & practices, and to attain the professionalisms. 12. Work with multi-tasking professionals and multidisciplinary team. 13. Prepare a technical report, to improve presentation and other soft skills.

COURSE CONTENT

Exposure to real life problems at various reputed industries engaged in areas of Computer Science and Engineering

Artificial Intelligence Learning Schedule L T P C


COURSE DESCRIPTION Artificial intelligence (AI) is a research field that studies how to realize the intelligent human behaviors on a computer. The main topics in Artificial intelligence include: problem solving, reasoning, planning, natural language understanding, computer vision, automatic programming, machine learning, and so on. In this course, student will study the most fundamental knowledge for understanding Artificial intelligence. Course will introduce some basic search algorithms for problem solving, knowledge representation and reasoning, pattern recognition, fuzzy logic and neural networks.


1. learn and possess a firm grounding in the existing techniques and component areas of Artificial Intelligence

2. apply this knowledge to the development of Artificial Intelligent Systems and to the exploration of research problems.


1. understand the principles of problem solving and be able to apply them successfully 2. be familiar with techniques for computer-based representation and manipulation of complex

information, knowledge, and uncertainty 3. gain awareness of several advanced AI applications and topics such as intelligent agents, planning

and scheduling, ma-chine learning, etc.


Introduction to Artificial Intelligence, Foundations and History of Artificial Intelligence, Applications of Artificial Intelligence, Intelligent Agents, Structure of Intelligent Agents. Computer vision, Natural Language Possessing. Unit II: Introduction to Search Searching for solutions, Uniformed search strategies, Informed search strategies, Local search algorithms and optimistic problems, Adversarial Search, Search for games, Alpha - Beta pruning. Unit III: Knowledge Representation & Reasoning Propositional logic, Theory of first order logic, Inference in First order logic, Forward & Backward chaining, Resolution, Probabilistic reasoning, Utility theory, Hidden Markov Models (HMM), Bayesian Networks. Unit IV: Machine Learning Supervised and unsupervised learning, Decision trees, Statistical learning models, Learning with complete data - Naive Bayes models, Learning with hidden data – EM algorithm, Reinforcement learning. Unit V: Pattern Recognition Introduction, Design principles of pattern recognition system, Statistical Pattern recognition, Parameter estimation methods - Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA), Classification Techniques – Nearest Neighbour (NN) Rule, Bayes Classifier, Support Vector Machine (SVM), K – means clustering. TEXT BOOKS

1. Artificial Intelligence – A Modern Approach - Stuart Russell and Peter Norvig, Pearson Education. 2. Artificial Intelligence - Elaine Rich and Kevin Knight, McGraw-Hill

REFERENCE BOOKS 1. Introduction to Artificial Intelligence - E Charniak and D McDermott, Pearson Education 2. Artificial Intelligence and Expert Systems - Dan W. Patterson, Prentice Hall of India

Software Project Management Learning Schedule L T P C

Pre-requisites: Software Engineering 3 0 0 3

COURSE DESCRIPTION This course is an introduction to the basic processes of project management for instructional design projects. Students will be introduced to organizational issues, methods of planning, and techniques for managing the business and creative processes that determine the success of a project. Students will learn to use project management software for organizing, scheduling and monitoring project progress. The experiences provided in the class will provide “real-world” examples and ask students to apply and expand their student‟s academic program of study. The overall purpose of the class is to blend theoretical aspects of project management to the pragmatic situations the student will face in industry or in academic environments. The outcome of the course will provide the foundation for developing technology-based project plans, management and experience in project management


1. define and highlight importance of software project management 2. describe the software project management activities 3. train software project managers and other individuals involved in software project 4. planning and tracking and oversight in the implementation of the software project management

process.


1. describe and determine the purpose and importance of project management from the perspectives of planning, tracking and completion of project

2. compare and differentiate organization structures and project structures 3. implement a project to manage project schedule, expenses and resources with the application of

suitable project management tools.

COURSE CONTENT Unit I: Introduction and Software Project Planning

Fundamentals of Software Project Management (SPM), Need Identification, Vision and Scope document, Project Management Cycle, SPM Objectives, Management Spectrum, SPM Framework, Software Project Planning, Planning Objectives, Project Plan, Types of project plan, Structure of a Software Project Management Plan, Software project estimation, Estimation methods, Estimation models, Decision process. Unit II: Project Organization and Scheduling Project Elements, Work Breakdown Structure (WBS), Types of WBS, Functions, Activities and Tasks, Project Life Cycle and Product Life Cycle, Ways to Organize Personnel, Project schedule, Scheduling Objectives, Building the project schedule, Scheduling terminology and techniques, Network Diagrams: PERT, CPM, Bar Charts: Milestone Charts, Gantt Charts. Unit III: Project Monitoring and Control Dimensions of Project Monitoring & Control, Earned Value Analysis, Earned Value Indicators: 23 Budgeted Cost for Work Scheduled (BCWS), Cost Variance (CV), Schedule Variance (SV), Cost Performance Index (CPI), Schedule Performance Index (SPI), Interpretation of Earned Value Indicators, Error Tracking, Software Reviews, Types of Review: Inspections, Deskchecks, Walk through, Code Reviews, Pair Programming. Unit IV: Software Quality Assurance and Testing Testing Objectives, Testing Principles, Test Plans, Test Cases, Types of Testing, Levels of Testing, Test Strategies, Program Correctness, Program Verification & validation, Testing Automation & Testing Tools, Concept of Software Quality, Software Quality Attributes, Software Quality Metrics and Indicators, The SEI Capability Maturity Model CMM), SQA Activities, Formal SQA Approaches: Proof of correctness,

Statistical quality assurance, Clean room process. Unit V: Project Management and Project Management Tools Software Configuration Management: Software Configuration Items and tasks, Baselines, Plan for Change, Change Control, Change Requests Management, Version Control, Risk Management: Risks and risk types, Risk Breakdown Structure (RBS), Risk Management Process: Risk identification, Risk analysis, Risk planning, Risk monitoring, Cost Benefit Analysis, Software Project Management Tools: CASE Tools, Planning and Scheduling Tools, MS-Project.

TEXT BOOKS

1. “Project Management: The Managerial Process with MS” - Clifford F. Gray and Erik W. Larson, Mc Graw Hill

REFERENCE BOOKS 1. Software Project Management - M. Cotterell, Tata McGraw-Hill Publication. 2. Software Project Management - Royce, Pearson Education 3. Software Project Management - Kieron Conway, Dreamtech Press 4. Software Project Management - S. A. Kelkar, PHI Publication.

Image processing and Pattern Recognition Learning Schedule L T P C

Pre-requisites: AI 3 0 0 3

COURSE DESCRIPTION This course is a graduate-level introductory course to the fundamentals of digital image processing and the theory of pattern recognition. It emphasizes general principles of image processing, rather than specific applications. Lectures will cover topics such as point operations, color processing, image thresholding/segmentation, morphological image processing, image filtering and DE convolution, noise reduction and restoration, scale-space techniques, feature extraction and recognition, image registration, and image matching. This course includes foundations of pattern recognition algorithms and machines, including statistical and structural methods. Data structures for pattern representation, feature discovery and selection, classification vs. description, parametric and non-parametric classification.


1. imparts knowledge in the area of image and image processing 2. understand fundamentals of digital image processing 3. provide knowledge of the applications of the theories taught in Digital Image Processing 4. learn the fundamentals of Pattern recognition and to choose an appropriate feature 5. classification algorithm for a pattern recognition problems and apply them properly using modern

computing tools such as Matlab, C/C++ etc.


1. understand Basics of Image formation and transformation using sampling and quantization 2. understand different types signal processing techniques used for image sharpening and smoothing 3. perform and apply compression and coding techniques used for image data 4. understand the nature and inherent difficulties of the pattern recognition problems 5. understand concepts, trade-offs, and appropriateness of the different feature types and classification

techniques such as Bayesian, maximum-likelihood, etc 6. select a suitable classification process, features, and proper classifier to address a desired pattern

recognition problem.

COURSE CONTENT Unit I: Introduction to Image Processing

Image formation, image geometry perspective and other transformation, stereo imaging elements of visual perception. Digital Image-sampling and quantization serial & parallel Image processing. Unit II: Image Restoration Image Restoration-Constrained and unconstrained restoration Wiener filter , motion blur remover, geometric and radiometric correction Image data compression-Huffman and other codes transform compression, predictive compression two tone Image compression, block coding, run length coding, and contour coding. Unit III: Segmentation Techniques Segmentation Techniques-thresh holding approaches, region growing, relaxation, line and edge detection approaches, edge linking, supervised and unsupervised classification techniques, remotely sensed image analysis and applications, Shape Analysis – Gestalt principles, shape number, moment Fourier and other shape descriptors, Skelton detection, Hough trans-form, topological and texture analysis, shape matching. Unit IV: Pattern Recognition Basics of pattern recognition, Design principles of pattern recognition system, Learning and adaptation, Pattern recognition approaches, Mathematical foundations – Linear algebra, Probability Theory, Expectation, mean and covariance, Normal distribution, multivariate normal densities, Chi squared test. Unit V: Statistical Patten Recognition Bayesian Decision Theory, Classifiers, Normal density and discriminant functions, Parameter estimation

methods: Maximum-Likelihood estimation, Bayesian Parameter estimation, Dimension reduction methods - Principal Component Analysis (PCA), Fisher Linear discriminant analysis, Expectation-maximization (EM), Hidden Markov Models (HMM),Gaussian mixture models.

TEXT BOOKS

1. Digital Image Processing - Ganzalez and Wood, Addison Wesley, 1993. 2. Fundamental of Image Processing - Anil K.Jain, Prentice Hall of India. 3. Pattern Classification - R.O. Duda, P.E. Hart and D.G. Stork, Second Edition John Wiley, 2006

REFERENCE BOOKS

1. Digital Picture Processing - Rosenfeld and Kak, vol.I & vol.II, Academic,1982 2. Computer Vision - Ballard and Brown, Prentice Hall, 1982 3. An Introduction to Digital Image Processing - Wayne Niblack, Prentice Hall, 1986 4. Pattern Recognition and Machine Learning - C. M. Bishop, Springer, 2009. 5. Pattern Recognition - S. Theodoridis and K. Koutroumbas, 4th Edition, Academic Press,2009

Real Time System Learning Schedule L T P C

Pre-requisites: OS 3 0 0 3

COURSE DESCRIPTION This course covers the principles of real-time systems, Modeling of a Real-Time System, Task assignment and scheduling, Resource management, Real-time operating systems, RTOS services, Programming language with real-time support, System design techniques, Inter task communication, Fault tolerant techniques, Reliability evaluation methods; Performance analysis, Case studies of real-time systems.


7. develop an understanding of various Real Time systems Application 8. obtain a broad understanding of the technologies and applications for the emerging and exciting

domain of real-time systems 9. get in-depth hands-on experience in designing and developing a real operational system.


1. understand concepts of Real-Time systems and modeling 2. recognize the characteristics of a real-time system 3. understand and develop document on an architectural design of a real-time system 4. develop and document Task scheduling, resource management, real-time operating systems and fault

tolerant applications of Real-Time Systems.


Definition, Typical Real Time Applications: Digital Control, High Level Controls, Signal Processing etc., Release Times, Dead-lines, and Timing Constraints, Hard Real Time Systems and Soft Real Time Systems, Reference Models for Real Time Systems: Processors and Resources, Temporal Parameters of Real Time Workload, Periodic Task Model, Precedence Constraints and Data Dependency. Unit II: Real Time Scheduling Common Approaches to Real Time Scheduling: Clock Driven Approach, Weighted Round Robin Approach, Priority Driven Approach, Dynamic Versus Static Systems, Optimality of Effective-Deadline-First (EDF) and Least-Slack-Time-First (LST) Algorithms, Rate Monotonic Algorithm, Offline Versus Online Scheduling, Scheduling Aperiodic and Sporadic jobs in Priority Driven and Clock Driven Systems. Unit III: Resources Sharing Effect of Resource Contention and Resource Access Control (RAC), Non-preemptive Critical Sections, Basic Priority-Inheritance and Priority-Ceiling Protocols, Stack Based Priority- Ceiling Protocol, Use of Priority-Ceiling Protocol in Dynamic Priority Systems, Preemption Ceiling Protocol, Access Control in Multiple-Module Resources, Controlling Concurrent Accesses to Data Objects. Unit IV: Real Time Communication Basic Concepts in Real time Communication, Soft and Hard RT Communication systems, Model of Real Time Communication, Priority-Based Service and Weighted Round-Robin Service Disciplines for Switched Networks, Medium Access Control Protocols for Broadcast Networks, Internet and Resource Reservation Protocols. Unit V: Real Time Operating Systems and Databases Features of RTOS, Time Services, UNIX as RTOS, POSIX Issues, Characteristic of Temporal data, Temporal Consistency, Con-currency Control, Overview of Commercial Real Time databases.

TEXT BOOKS 1. Real Time Systems - Jane W. S. Liu, Pearson Education Publication

REFERENCE BOOKS

1. Real Time Systems - Mall Rajib, Pearson Education 2. Real-Time Systems: Scheduling, Analysis, and Verification - Albert M. K. Cheng, Wiley.

Cloud Computing Learning Schedule L T P C

Pre-requisites: OS and CN 3 1 0 4

COURSE DESCRIPTION This course provides a hands-on comprehensive study of Cloud concepts and capabilities across the various Cloud service models including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Business Process as a Service (BPaaS). IaaS topics start with a detailed study the evolution of infrastructure migration approaches from VMWare/Xen/ KVM virtualization, to adaptive virtualization, and on-demand resources provisioning. PaaS topics cover a broad range of Cloud vendor platforms including Google App Engine, Microsoft Azure, OpenStack and others as well as a detailed study of related platform services such as storage services that leverage Google Storage, Amazon S3, Amazon Dynamo, or other services meant to provide Cloud resources management and monitoring capabilities. The SaaS and PaaS topics covered in the course will familiarize students with the use of vendor-maintained applications and processes available on the Cloud on a metered on-demand basis in multi-tenant environments. The course also covers the Cloud security model and associated challenges and delves into the implementation and support of High Performance Computing and Big Data support capabilities on the Cloud. Through hands-on assignments and projects, students will learn how to configure and program IaaS services. COURSE OBJECTIVES The objective of this course is to:

1. learn cloud computing delivery model IaaS 2. learn cloud computing delivery model PaaS 3. learn cloud computing delivery model SaaS.


1. understand Cloud delivery models in details 2. understand briefly Cloud Computing Reference Architecture.

COURSE CONTENT Unit I: Introduction of delivery models in Cloud Computing

Introduction to cloud delivery models, List various cloud delivery models, Advantages of delivery models in cloud, trade-off in cost to install versus flexibility, Cloud service model architecture. Unit II: Infrastructure as a Service (IaaS) Introduction to Infrastructure as a Service delivery model, characteristics of IaaS, Architecture, examples of IaaS, Applicability of IaaS in the industry. Unit III: Platform as a Service (PaaS Introduction to Platform as a Service delivery model, characteristics of PaaS, patterns, architecture and examples of PaaS, Applicability of PaaS in the industry. Unit IV: Software as a Service (SaaS) Introduction to Software as a Service delivery model, characteristics of SaaS, Architecture, examples of SaaS, Applicability of SaaS in the industry. Unit V: Cloud computing Reference Architecture (CCRA) Introduction to Cloud computing reference architecture (CCRA), benefits of CCRA, Architecture overview, versions and application of CCRA for developing clouds.

TEXT BOOKS

1. Cloud Computing Architecture (IBM ICE) REFERENCE BOOKS

1. Cloud computing for Dummies (November 2009) Judith Hurwitz, Robin Bloor, Marcia Kaufman, Fern Halper

2. IBM Cloud Computing http://www.ibm.com/cloud-computing/us/en/ 3. Wikipedia page on Cloud Computing http://en.wikipedia.org/wiki/Cloud_computing.

http://www.ibm.com/cloud-computing/us/en/

http://en.wikipedia.org/wiki/Cloud_computing

Bioinformatics Learning Schedule L T P C

Pre-requisites: Basics of IT 3 0 0 3

COURSE DESCRIPTION This course will provide an overview of bioinformatics, covering a broad selection of the most important techniques used to analyze biological sequence and expression data. Students will acquire a working knowledge of bioinformatics applications through hands-on use of software to ask and answer biological questions. In addition, the course will provide students with an introduction to the theory behind some of the most important algorithms used to analyze sequence data (for example, alignment algorithms and the use of hidden Markov models). Topics covered will include protein and DNA sequence alignments, evolutionary analysis and phylogenetic trees, obtaining protein secondary structure from sequence, and analysis of gene expression including clustering methods.


1. impart knowledge on basic techniques of Bioinformatics and on analysis of biological data using computational methods

2. investigating problems in molecular and biology from a computational perspective.


1. extract information from different types of bioinformatics data (gene, protein, disease, etc.), including their biological characteristics and relationships

2. employ different data representation models and formats used for bioinformatics data representation, including markup languages such as SBML and CellML, and ontologies such as GO ontology

3. apply the different approaches used for data integration and data management, including data warehouse and wrapper approaches

4. analyze processed data with the support of analytical and visualization tool 5. Interact with non-bioinformatics professionals, such as biologists and biomedical researchers, to

better understand their bioinformatics needs for improved support and service delivery 6. design and develop bioinformatics solutions by adapting existing tools, designing new ones or a

combination of both.


Bioinformatics objectives and overviews, Interdisciplinary nature of Bioinformatics, Data integration, Data analysis, Major Bioinformatics databases and tools. Metadata: Summary 40 & reference systems, finding new type of data online. Molecular Biology and Bioinformatics: Systems approach in biology, Central dogma of molecular biology, problems in molecular approach and the bioinformatics approach, overview of the bioinformatics applications. Unit II: DNA Basic chemistry of nucleic acids, Structure of DNA, Structure of RNA, DNA Replication, -Transcription, - Translation, Genes- the functional elements in DNA, Analysing DNA, DNA sequencing. Proteins: Amino acids, Protein structure, Secondary, Tertiary and Quaternary structure, Protein folding and function, Nucleic acid-Protein interaction. Unit III: Applications for bioinformatics Perl Basics, Perl applications for bioinformatics- Bioperl, Linux Operating System, mounting/ unmounting files, tar, gzip / gunzip, telnet, ftp, developing applications on Linux OS, Understanding and Using Biological Databases, Overview of Java, CORBA, XML, Web deployment concepts. Unit IV: Biological data storage techniques Genome, Genomic sequencing, expressed sequence tags, gene expression, transcription factor binding sites and single nucleotide polymorphism. Computational representations of molecular biological data storage techniques: databases (flat, relational and object oriented), and controlled vocabularies, general data retrieval

techniques: indices, Boolean search, fuzzy search and neighboring, application to biological data warehouses. Unit V: Representation of patterns and relationships in bioinformatics Macromolecular structures, chemical compounds, generic variability and its connection to clinical data. Representation of patterns and relationships: sequence alignment algorithms, regular expressions, hierarchies and graphical models, Phylogenetic BLAST.

TEXT BOOKS

1 Fundamental concepts of Bioinformatics - D E Krane and M L Raymer, Pearson Education. 2 Bioinformatics Methods & applications, Genomics, Proteomics & Drug Discovery - Rastogi,

Mendiratta and Rastogi, PHI, New Delhi.

REFERENCE BOOKS 1. Bioinformatics: with fundamentals of genomics and proteomics - Shubha Gopal, et.al., Mc Graw Hill. 2. Developing Bio informatics computer skills - O‟Reilly, CBS. 3. Evolutionary Bioinformatics - Forsdyke, Springer.

Neural Networks Learning Schedule L T P C

Pre-requisites: CN 3 0 0 3

COURSE DESCRIPTION This course will cover basic neural network architectures and learning algorithms, for applications in pattern recognition, image processing, and computer vision. Three forms of learning will be introduced (i.e., supervised, unsupervised and reinforcement learning) and applications of these will be discussed. The students will have a chance to try out several of these models on practical problems.


1. make students familiar with basic concepts and tool used in neural networks 2. teach students structure of a neuron including biological and artificial 3. teach learning in network (Supervised and Unsupervised) 4. teach concepts of learning rules.


1. superior for cognitive tasks and processing of sensorial data such as vision, image- and speech recognition, control, robotics, expert systems

2. design single and multi-layer feed-forward neural networks 3. understand supervised and unsupervised learning concepts & understand unsupervised learning

using Kohonen networks 4. understand training of recurrent Hopfield networks and associative memory concepts.


Structure of biological neurons relevant to ANNs., Models of ANNs; Feedforward & feedback networks; learning rules; Hebbian learning rule, perception learning rule, delta learning rule, Widrow-Hoff learning rule, correction learning rule, Winner –lake all learning rule, etc. Unit II: Single layer Perception Classifier and Multi-layer Feed forward Networks Classification model, Features & Decision regions; training & classification using discrete perceptron, algorithm, single layer continuous perceptron networks for linearly separable classifications, linearly non-separable pattern classification, Delta learning rule for multi-perceptron layer, Generalized delta learning rule, Error back-propagation training, learning factors, Examples. Unit III: Single layer feedback Networks Basic Concepts, Hopfield networks, Training & Examples. Associative memories: Linear Association, Basic Concepts of recurrent. Unit IV: Auto associative memory Retrieval algorithm, storage algorithm; By directional associative memory, Architecture, Association encoding & decoding, Stability. Unit V: Self organizing networks UN supervised learning of clusters, winner-take-all learning, recall mode, Initialization of weights, seperability limitations. TEXT BOOKS

1. Introduction to Artificial Neural systems - Jacek M. Zurada, 1994, Jaico Publ. House REFERENCE BOOKS

1. Neural Networks :A Comprehensive formulation - Simon Haykin, 1998, AW 2. Neural Networks - Kosko, 1992, PHI. 3. Neural Network Fundamentals – N.K. Bose , P. Liang, 2002, T.M.H 4. Neural Network - T.N.Shankar, University Science Press 5. Neuro Fuzzy Systems - Lamba, V.K., University Science Press

Professional Ethics for B.Tech-Computer Science & Engineering

Learning Schedule L T P C

Pre-requisites: Universal Human Values 2 0 0 2

COURSE DESCRIPTION The methodology of this course is universally adaptable, involving a systematic and Inter-relationship of technology growth and social, economic and cultural growth. It is free from any dogma or value prescriptions. This subject mainly deals with workmanship culture, social and ethical responsibilities of Computer Science Engineers.

COURSE OBJECTIVES 1. To create an awareness in B.Tech-Computer Science & Engineering about Ethics in engineering

profession. 2. To understand professional responsibility of an engineer. 3. To appreciate ethical dilemma while discharging duties in professional life.

COURSE OUTCOMES On completion of this course, the students will be able to 1. Understand the significance of value inputs in a classroom and start applying them in their professional

life. 2. Understand the role of a human being in ensuring harmony in society and nature. 3. Distinguish between ethical and unethical practices, and start working out the strategy to actualize a

harmonious environment wherever they work.

COURSE CONTENTS

Unit I: Engineering knowledge as social and professional activities

Science, Technology and Engineering as knowledge and as social and professional activities. Inter-

relationship of technology growth and social, economic and cultural growth; historical perspective. Ancient,

medieval and modern technology/industrial revolution and its impact; the Indian Science and Technology.

Unit II: Social and human critiques of technology

Social and human critiques of technology; Mumford and Ellul. Rapid technological growth and Depletion of

resources; reports of the club of Rome; limits to growth; sustainable development. Energy crisis, renewable

energy resources. Environmental degradation and pollution; eco friendly Technologies; environmental

regulations; environmental ethics. Technology and the arms Race; the nuclear threat. Appropriate

technology movement of Schumacher; later developments.

Unit III: Technology and the developing nations

Technology and the developing nations; problems of technology transfer; technology. Assessment/impact

analysis. Human operator in engineering projects and industries; problems of

Man-machine interaction; impact of assembly line and automation; human centered technology.

Industrial hazards and safety; safety regulations, safety engineering.

Unit IV: Politics and technology

Politics and technology; authoritarian versus democratic control of technology; social and ethical audit of

industrial organizations.

Unit V: Engineering profession

Engineering profession; ethical issues in engineering practice; Conflicts between business demands and

professional ideals; social and ethical responsibilities of the engineer; codes of professional ethics; whistle

blowing and beyond; case studies.

TEXT BOOKS 1. Baum, R.J., ed, Ethical Problems in Engineering REFERENCE BOOKS

Beabout, G.R., Wennemann, D.J., Applied Professional Ethics

Neural Networks Lab Learning Schedule L T P C



5. make students familiar with basic concepts and tool used in neural networks 6. teach students structure of a neuron including biological and artificial 7. teach learning in network (Supervised and Unsupervised) 8. teach concepts of learning rules.


5. superior for cognitive tasks and processing of sensorial data such as vision, image- and speech recognition, control, robotics, expert systems

6. design single and multi-layer feed-forward neural networks 7. understand supervised and unsupervised learning concepts & understand unsupervised learning

using Kohonen networks 8. understand training of recurrent Hopfield networks and associative memory concepts.

LIST OF EXPERIMENTS 1. Study of Matlab 2. (a) Write a program to perform basic operations in Matlab

(b) To perform matrix operations in Matlab 3. (a) Introduction to script file in Matlab

(b) Write a program to calculate the factorial of a number by creating a script file by using while loop (c) Write a program in Matlab to find the factorial by creating a function file by using for loop

4. (a) Write a program in Matlab to plot multiple curves in single plot by creating a script file (b) Write a program in Matlab for plotting multiple curves in single figure

5. (a) Write a program in Matlab to plot Activation function used in neural network (b) Write a program in Matlab to plot piecewise continuous activation function (threshold and signum function in neural network)

6. (a) To realize gates using Mcculloh Pitt model in Matlab (b) Write a program to implement XOR gate using Mcclloh-Pitts neuron

7. (a) Write a program to create the Perceptron using GUI in Matlab (b) Write a program in Matlab to create `Perceptron using commands

8. (a) Write a program in Matlab to classify the Classes using Perceptron (b) Write a program in Matlab for Pattern Classification using Perceptron network

9. Write a program in Matlab for creating a Back Propagation Feed-forward neural network 10. To design a Hopfield Network which stores 4 vectors 11. Write a program to illustrate how the perception learning rule works for non-linearly separable problems 12. Write a program to illustrate Linearly non-separable vectors

Industrial/Research Project (Phase-I) Learning Schedule L T P C

Pre-requisites: Programming Language 0 0 2 5

COURSE OBJECTIVES 1. To develop the capacity of students in correlating theoretical knowledge into practical systems either

to perform creative works or to perform analysis and hence to suggest solutions to problems, pertaining to civil engineering domain.

2. Foster collaborative learning skills. 3. Develop self-directed inquiry and life-long skills. 4. To enhance the communication skills of the students by providing opportunities to discuss in groups

and to present their observations, findings and report in formal reviews both in oral and written format.

COURSE OUTCOMES

On completion of this course, the students will be able to 1. Submit a project synopsis comprising of the application and feasibility of the project. 2. Design a system, component, or process to meet desired needs within realistic constraints such as

economic, environmental, social, political, ethical, health care, safety and sustainability. 3. Work and communicate efficiently in multidisciplinary teams 4. Identify, formulate, and solve engineering problems. 5. Develop an understanding of professional and ethical responsibility.

COURSE CONTENT Project work is of duration of two semesters and is expected to be completed in the eighth semester. Each student group consisting of not more than five members is expected to design and develop a complete system or make an investigative analysis of a technical problem in the relevant area. The project batches are expected to fix their topics, complete preliminary studies like literature survey, field measurements etc. in the seventh semester.

Business Intelligence Learning Schedule L T P C

Pre-requisites: Cloud Computing 3 0 0 3

COURSE DESCRIPTION This course is intended to provide an integrative foundation in the field of business intelligence at the operational, tactical, and strategic levels. Topics such as value chain, customer service management, business process analysis and design, transaction processing systems, management information systems, and executive information systems will be covered, along with other topics relevant to the field of business intelligence. A critical success factor in Business Intelligence is the ability to communicate one‟s analyses and recommendations to decision-makers. In this capstone course, students are directed to prepare a thesis document that serves as a model for doing this effectively. Issues examined include writing an effective thesis statement, making logical arguments, the constraints imposed by media richness, and the limitations of transferring explicit knowledge.


1. learn Business Intelligence.


1. gain knowledge of Business Intelligence 2. build business projects 3. generate and manage BI reports 4. do BI Deployment, Administration & Security.

COURSE CONTENT Unit I: Introduction to Business Intelligence

Understanding the scope of today‟s BI solutions and how they fit into existing infrastructure Assessing new options such as SaaS and cloud-based technology. Describe BI, its components & architecture, previewing the future of BI Crafting a better experience for all business users, End User Assumptions, Setting up Data for BI, The Functional Area of BI Tools, Query Tools and Reporting, OLAP and Advanced Analytics, Supporting the requirements of senior executives, including performance management. Unit II: Elements of Business Intelligence Solutions Reports & ad hoc queries; Analyse OLAP data; Dashboards & Scorecards development, Metadata Models; Automated tasks & events; Mobile & disconnected BI; Collaboration capabilities; Real time monitoring capabilities; Software development kit; Consume BI through portals, web applications, Desktop applications. Unit III: Building the BI Project Planning the BI project, Project Resources; Project Tasks, Risk Management and Mitigation, Cost-justifying BI solutions and measuring success, Collecting User Requirements, Requirements-Gathering Techniques; Prioritizing & Validating BI Requirements, Changing Requirements; BI Design and Development, Best Practices for BI Design; Post- Implementation Evaluations, Maintaining Your BI Environment. Unit IV: Reporting authoring Building reports with relational vs Multidimensional data models ; Types of Reports - List, crosstabs, Statistics, Chart, map, financial etc; Data Grouping & Sorting, Filtering Reports, Adding Calculations to Reports, Conditional formatting, Adding Summary Lines to Reports. Drill up, drill- down, drill-through capabilities. Run or schedule report, different output forms – PDF, excel, csv, xml etc. Unit V: BI Deployment, Administration & Security Centralized Versus Decentralized Architecture, BI Architecture Alternatives, phased & incremental BI roadmap, System Sizing, Measurements and Dependencies, System Sizing, Measurements, and Dependencies. Setting Early Expectations and Measuring the Results. End-User Provisos. OLAP

Implementations. Expanding BI Authentication Authorization, Access Permissions, Groups and Roles, Single-sign on Server Administration, Manage Status & Monitoring, Audit, Mail server & Portal integration, Back Up and Restore.

TEXT BOOKS

1. Business Intelligence (IBM ICE Publication).

REFERENCE BOOKS 1. http://en.wikipedia.org/wiki/Business_intelligence. 2. http://www.webopedia.com/TERM/B/Business_Intelligence.html. 3. Http://www.cio.com/article/40296/Business_Intelligence_Definition_and_Solutions.

http://en.wikipedia.org/wiki/Business_intelligence

http://www.webopedia.com/TERM/B/Business_Intelligence.html

http://www.cio.com/article/40296/Business_Intelligence_Definition_and_Solutions

Android Apps Development Learning Schedule L T P C

Pre-requisites: Java 3 0 0 3

COURSE DESCRIPTION This course provides a basic understanding of Android development, including the use of content providers, creating audio and video services. This course focuses on helping people become an Android application developer and releasing high-quality apps to the marketplace. Learn about the various stages of development on the Android platform and study topics related to UI, application services, permissions and security, graphics and video resources, data persistence, monitoring tools, mobile app marketing, application hosting and more. Develop core Java development skills while you explore key concepts for building rich applications using advanced features. Learn from instructors and guest speakers working in the industry.


1. learn the set up and installation of Android 2. learn Android App development 3. learn user interfaces and Controls.


1. gain knowledge of set up and installation of Android 2. gain App development knowledge 3. gain knowledge of user interfaces on Mobile Apps.

COURSE CONTENT Unit I: Installation and Setup on Android

Environment Setup – Installation & Setup of SDK tools on Windows; Installing platforms and samples; Creating an Android Virtual Device (emulator); Installing Eclipse on a Windows machine; Installing the Android Development Tools; Preparing an Android device for development. Unit II: Android App Development Overview of Android development; Understanding project creation and structure; Working with the AndroidManifest.xml file; Creating and managing activities; Using explicit intents; Using implicit intents; Creating and using resources; Understanding security and permissions; Debugging an app. Unit III: User interface and Controls Understanding units and layout; Using layout managers; Working with text controls; Building button controls; Building list controls; Building custom list layouts; Other interesting controls. Unit IV: Graphics and Animation Creating and using styles; Creating and using themes ; Creating icons; Creating NinePatch drawables, Setting up frame-by-frame animation; Showing tween animation; Working in 2D graphics. Unit V: Supporting Multiple Screens Understanding screen size and density; Providing alternate layouts.

TEXT BOOKS

1. Mobile Apps for Android (IBM ICE).

REFERENCE BOOKS 4. David Tainar - Mobile Computing: Concepts Methodologies, Tools & Applications. 5. Barbara L Ciaramtaro - Mobile technology consumption.

Data Mining and Data Warehousing Learning Schedule L T P C

Pre-requisites: DBMS 3 1 0 4

COURSE DESCRIPTION Data mining is a class of analytical techniques that examine a large amount of data to discover new and valuable information. This course is designed to introduce the core concepts of data mining, its techniques, implementation, benefits, and outcome expecta-tions from this new technology. It will also identify industry branches which most benefit from DM.Data warehousing involves data preprocessing, data integration, and providing on-line analytical processing (OLAP) tools for the interactive analysis of multidimensional data, which facilitates effective data mining. This course introduces data warehousing and data mining techniques and their software tools. Topics include: data warehousing, association analysis, classification, cluster-ing, numeric prediction, and selected advanced data mining topics.

COURSE OBJECTIVES


6. Introduce data mining principles and techniques. 7. Introduce data mining as a cutting edge business intellegence tool. 8. Develop and apply critical thinking, problem solving and decision making skills. 9. Introduce the concepts of Data Warehousing, difference between database and data warehousing. 10. Describe and demonstrate basic data mining algorithms, methods, tools, 11. Describe ETL Model and the Star Schema to design a Data Warehouse.

COURSE OUTCOMES


4. Design a data warehouse or data mart to present information needed by the and can be utilized for

managing clients. 5. Design and implement a quality data warehouse or data mart effectively and administer the data

resources in such a way that it will truly meet management‟s requirements. 6. Evaluate standards and new technologies to determine their potential impact on your information

resource for a large complex data warehouse/data mart. 7. Use data mining tools for projects and to build reliable products as per demand.

COURSE CONTENT

Unit I

Overview, Motivation(for Data Mining),Data Mining-Definition & Functionalities, Data Processing, Form of Data Preprocess-ing, Data Cleaning: Missing Values, Noisy Data, (Binning,Clustering, Regression, Computer and Human inspection),Inconsistent Data, Data Integration and Transformation. Data Reduction:- Data Cube Aggregation, Dimensionality reduction, Data 35 Com-pression, Numerosity Reduction, Clustering, Discretization and Concept hierarchy generation Unit II Concept Description:- Definition, Data Generalization, Analytical Characterization, Analysis of attribute relevance, Mining Class comparisions, Statistical measures in large Databases. Measuring Central Tendency, Measuring Dispersion of Data, Graph Dis-plays of Basic Statistical class Description, Mining Association Rules in Large Databases, Association rule mining,mining Single-Dimensional Boolean Association rules from Transactional Databases– Apriori Algorithm, Mining Multilevel Association rules from Transaction Databases and Mining Multi-Dimensional Association rules from Relational Databases Unit III Classification and Predictions: What is Classification & Prediction, Issues regarding Classification and prediction, Decision tree, Bayesian Classification, Classification by Back propagation, Multilayer feed- forward Neural Network, Back propagation Algo-rithm, Classification methods K-nearest neighbor

classifiers, Genetic Algorithm. Cluster Analysis: Data types in cluster analysis, Categories of clustering methods, Partitioning methods. Hierarchical Clustering- CURE and Chameleon, Density Based Methods- DBSCAN, OPTICS, Grid Based Methods- STING, CLIQUE, Model Based Method –Statistical Approach, Neural Network approach, Outlier Analysis Unit IV Data Warehousing: Overview, Definition, Delivery Process, Difference between Database System and Data Warehouse, Multi Dimensional Data Model, Data Cubes, Stars, Snow Flakes, Fact Constellations, Concept hierarchy, Process Architecture, 3 Tier Architecture, Data Marting. Unit V Aggregation, Historical information, Query Facility, OLAP function and Tools. OLAP Servers, ROLAP, MOLAP, HOLAP, Data Mining interface, Security, Backup and Recovery, Tuning Data Warehouse, Testing Data Warehouse.

TEXT BOOKS

1. M.H.Dunham,”Data Mining:Introductory and Advanced Topics” Pearson Education. 2. Sam Anahory, Dennis Murray, “Data Warehousing in the Real World : A Practical Guide for

Building Decision Support Systems, Pearson Education.

REFERENCE BOOKS 1. Jiawei Han, Micheline Kamber, ”Data Mining Concepts & Techniques” Elsevier. 2. Mallach,”Data Warehousing System”,McGraw –Hill.

Android Apps Development Lab Learning Schedule L T P C

Pre-requisites: JAva 0 0 2 1


1. develop basic Android application 2. creating Activities 3. using Intents for activity communication 4. develop the GUI application.


1. understand android application hierarchy, UI components and their purpose 2. create activity, do activity to activity communication using intents and transfer data between/among

intents. 3. apply style to android UI components 4. able to use and implement menus, notifications & implement notification using Notification

Compact Builder class 5. configure and implement context menu and option menu as a part of android app. 6. deploy and test the applications using Android AVD.

LIST OF EXPERIMENTS

1. Create a basic Android application 2. Working with forms 3. Android App- working with intents 4. Apply style and theme in an android app 5. Create an Android app that does payment process via a context menu 6. Create an Android app that does a currency converter operations using an options menu 7. Create an Android notification app that displays notification about the messages received 8. Create an Android app for sending data from first activity to second activity. 9. Create an Android app for getting result from second activity (Using startActivityForResult) 10. Create an Android app for storing user data using SQLITE

Industrial/Research Project (Phase-II) Learning Schedule L T P

Pre-requisites: Programming Language 0 0 2

COURSE OBJECTIVES 1. To develop the capacity of students in correlating theoretical knowledge into

practical systems either to perform creative works or to perform analysis and hence to suggest solutions to problems, pertaining to civil engineering domain.

2. Foster collaborative learning skills. 3. Develop self-directed inquiry and life-long skills. 4. To enhance the communication skills of the students by providing

opportunities to discuss in groups and to present their observations, findings and report in formal reviews both in oral and written format.

COURSE OUTCOMES

On completion of this course, the students will be able to 1. Submit a project synopsis comprising of the application and feasibility of the

project. 2. Design a system, component, or process to meet desired needs within

realistic constraints such as economic, environmental, social, political, ethical, health care, safety and sustainability.

3. Work and communicate efficiently in multidisciplinary teams 4. Identify, formulate, and solve engineering problems. 5. Develop an understanding of professional and ethical responsibility.

COURSE CONTENT Project work is of duration of two semesters and is expected to be completed in the eighth semester. Each student group consisting of not more than five members is expected to design and develop a complete system or make an investigative analysis of a technical problem in the relevant area. The project batches are expected to fix their topics, complete preliminary studies like literature survey, field measurements etc. in the seventh semester.

B.Tech-Computer Science & Engineering SEMESTER III

Professional Skills

1. Name of the Department – CENTRE FOR LANGUAGES AND COMMUNICATION 2. Course Name Professional Skills

L - 1 T – 0 P -2

3. Course Code 13020318 4. Type of Course (use tick mark) Core (√) PE() OE() 5. Pre-requisite (if

any) Proficiency in English

6. Frequency (use tick marks)

Even () Odd (√) Either Sem ()

Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 14 Tutorials = 0 Practical = 28 8. Brief Syllabus Unit-1: Listening and Speaking Comprehension: Greetings and self introduction, Review of Animated mute short stories, Audio clippings followed one response questionnaire Unit-2: Vocabulary Building and Pronunciation: Introduction to app based dictionary-Merriam Webster, process of making a digital of dictionary Understanding of Syllable, Stress, Pitch, and Intonation with PRAAT (software for speech analysis), Word building with compounding process Unit-3: Speaking Comprehension: Introduction to language used in social networking- code mixing and code switching, Panel Discussion with tug of words, Fish bowl technique, Situation based dialogues. Spontaneous throw of ideas leading to problem solving, situation based dialogues, case studies. ‘Thought of the day’/ ‘question of the day’ to enhance critical thinking and spontaneous speaking Unit-4: Reading Comprehension: Introduction to essence of reading. Types of Reading, Extensive reading session of newspaper, excerpt, articles, stories, critical analysis on reading abstracts. Making a digital newspaper with innovative categories. Unit-5: Writing Comprehension: Diary entry for emotional expression, Introduction to Paragraphs, Essays, Short stories, Articles, Jest of academic writing: Reports, Proposal, Dissertation, Thesis, Letters, Emails, Note taking, Note making 9. Learning objectives:

1. Enhancing listening-speaking Skills 2. Enhancement of Vocabulary and Pronunciation Skills. 3. Enhancement of Debating Skills which will further enhance public speaking Skills 4. Induce Reading and Thinking ability 5. Enhancing skills pertaining to industry

10. Course Outcomes (COs):

1. Able to convey their ideas in an expressive and effective way 2. Able to speak confidently before the audience 3. Able to get a holistic industry perspectives 4. Able to think out of the box and express 5. Able to write effectively

11. Unit wise detailed content Unit-1 Number of lectures

= 4 Title of the unit: Listening and Speaking Comprehension

Listening and Speaking Comprehension: Greetings and self introduction, Review of Animated mute short stories, Audio clippings followed one response questionnaire Unit – 2 Number of lectures Title of the unit: : Vocabulary Building and Pronunciation

14. Tutorial / Extended Tutorial /presentation/Case study components

= 4 Unit-2: Vocabulary Building and Pronunciation: Introduction to app based dictionary-Merriam Webster, process of making a digital of dictionary Understanding of Syllable, Stress, Pitch, and Intonation with PRAAT (software for speech analysis), Word building with compounding process Unit – 3 Number of lectures

= 4 Title of the unit: Speaking Comprehension

Unit-3: Speaking Comprehension: Introduction to language used in social networking- code mixing and code switching, Panel Discussion with tug of words, Fish bowl technique, Situation based dialogues. Spontaneous throw of ideas leading to problem solving, situation based dialogues, case studies. Unit – 4 Number of lectures

= 4 Title of the unit: Reading Comprehension

Unit-4: Reading Comprehension: Introduction to essence of reading. Types of Reading, Extensive reading session of newspaper, excerpt, articles, stories, critical analysis on reading abstracts. Making a digital newspaper with innovative categories. Unit – 5 Number of lectures

= 4 Title of the unit: Writing Comprehension

Unit-5: Writing Comprehension: Paragraphs, Essays, Short stories, Articles, Reports, Proposal, Dissertation, Thesis, Letters, Emails, Note taking, Note making 12. Brief Description of self learning / E-learning component

Students can practice from various sites online for Aptitude Building Questions. https://www.indiabix.com/, https://www.indiabix.com/online-test/aptitude-test , https://www.crazyengineers.com › ... › Engineering Jobs & Career Advice, https://testbook.com/aptitude etc. The students will be encouraged to learn using the SGT ELearning portal and choose the relevant lectures delivered by subject experts of SGT University.

The link to the E-Learning portal: https://elearning.sgtuniversity.ac.in/course-category/general/

13. Books Recommended (3 Text Books + 2-3 Reference Books) 1. Improve your Writing, V.N. Arora, Lakshmi Chandra, Oxford University Press, New Delhi 2014

2. Technical Communication Principles and Practice’, Meenakshi Raman and Sangeeta Sharma, Oxford University Press 2012

3. Communication Skills in English, D. G. Saxena and Kuntal Tamang, Top Quark, 2011

cue

4. ‘Essential English Grammar’,Raymond Murphy, Cambridge University Press 1998

5. Business Communication Connecting at Work’ Hory Sankar Mukerjee, Oxford University Press 2013

Sr. No. Title CO covered

https://www.indiabix.com/

https://www.indiabix.com/online-test/aptitude-test

https://testbook.com/aptitude

https://elearning.sgtuniversity.ac.in/course-category/general/

15. Lab component components

Sr. No. Title CO covered

1 Conversational Practices through listening Exercises

2 Vocabulary Building Exercises

3 Speaking Tests Online

4 Reading Articles and Related Exercises

5 Professional Writing Tasks

1 Review of movie and newspaper clippings

2 Perfection in Pronunciation , Vocabulary Building Exercises

3 Role Plays and Panel Discussions

4 Report Writing on Industry Visits and Internships

5 Letter Writing / Official Correspondence, Presentation on Projects Undertaken

6 Dialogue Writing

SEMESTER III

Data Structures using C

1. Name of the Department: FET 2. Course Name Data Structures

using C L-3 T-0 P-2


any) 6. Frequency (use tick

marks) Even () Odd (√) Either

Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28 8. Brief Syllabus: An Introduction to data structure, Time and space complexity, Arrays and link list, Sparse

Matrix Stacks and Queues- Insertion, Deletion, Traversing algorithms, Arithmetic expressions Trees- Terminologies, Binary Tree, Traversals, Huffman Algorithms Graphs- BFS, DFS, Dijkstra and Warshall Algorithm Searching and Sorting- Linear and Binary search, Sorting methods and their complexity, BST, AVL, B-tree, m-

way tree, Hashing techniques 9. Learning objectives: To Learn concepts of various data structure to solve relative problems. 10. Course Outcomes:

1) Use and implement appropriate data structure for the required problems using a programming language such as

C/C++. 2) Analyze step by step and develop algorithms to solve real world problems. 3) Implementing various data structures viz. Stacks, Queues, Linked Lists, Trees and Graphs.

4) Understand various searching & sorting techniques.


= 10 Title of the unit: Introduction – Basic Terminology

Elementary Data Organization, Algorithm, Efficiency of an Algorithm, Time and Space Complexity, Asymptotic notations: Big-Oh, Time-Space trade-off. Abstract Data Types (ADT)Arrays: Definition, Single and Multidimensional Arrays, Representation of Arrays : Row Major Order, and Column Major Order, Application of arrays, Sparse Matrices and their representations. Linked lists: Array Implementation and Dynamic Implementation of Singly Linked Lists, Doubly Linked List, Circularly Linked List, Operations on a Linked List. Insertion, Deletion, Traversal, Polynomial Representation and Addition, Generalized Linked List. Unit - 2 Number of lectures

= 8 Title of the unit: Stacks and Queues

Primitive Stack operations: Push & Pop, Array and Linked Implementation of Stack in C, Application of stack: Prefix and Postfix Expressions, Evaluation of postfix expression, Recursion, Tower of Hanoi Problem, Simulating Recursion, Principles of recursion, Tail recursion, Removal of recursion Queues, Operations on Queue: Create, Add, Delete, Full and Empty, Circular queues, Array and linked implementation of queues in C, Dequeue and Priority Queue.

Unit - 3 Number of lectures = 8

Title of the unit: Trees

Binary Trees, Binary Tree Representation: Array Representation and Dynamic Representation, Complete Binary Tree, Algebraic Expressions, Extended Binary Trees, Array and Linked Representation of Binary trees, Tree Traversal algorithms: Inorder, Preorder and Postorder, Threaded Binary trees, Traversing Threaded Binary trees, Huffman algorithm. Unit - 4 Number of lectures

= 8 Title of the unit: Graphs

Terminology, Sequential and linked Representations of Graphs: Adjacency Matrices, Adjacency List, Adjacency Multi list, Graph Traversal : Depth First Search and Breadth First Search, Connected Component, Spanning Trees, Minimum Cost Spanning Trees: Prims and Kruskal algorithm. Transitive Closure and Shortest Path algorithm: Warshal Algorithm and Dijikstra Algorithm, Introduction to Activity Networks. Unit - 5 Number of lectures

= 8 Title of the unit: Searching and Sorting

Sequential search, Binary Search, Comparison and Analysis Internal Sorting: Insertion Sort, Selection, Bubble Sort, Quick Sort, Two Way Merge Sort, Heap Sort, Radix Sort, Practical consideration for Internal Sorting. Search Trees: Binary Search Trees(BST), Insertion and Deletion in BST, Complexity of Search Algorithm, AVL trees, Introduction to m-way Search Trees, B Trees & B+ Trees Hashing: Hash Function, Collision Resolution Strategies Storage Management: Garbage Collection and Compaction. 12. Brief Description of self learning / E-learning component. This learning method gives students to find out their learning capability. Students involve some sort of choice in

this learning. As self directed learning learners can determine which modules or scenarios to review again and again.

13. Books Recommended (1 Text Book + 2 Reference Books)

• Fundamentals of Data Structures - Horowitz and Sahani, Galgotia Publication

• Data Structures - Lipschutz, Schaum’s Outline Series, TMH

• Data Structures Using C and C++ - Aaron M. Tenenbaum, Yedidyah Langsam and Moshe J. Augenstein, PHI Publications

Lab Components Sr. No. Title CO covered 1 Revision of programs of Data Structures from pervious semester: Insertion

Sort, Bubble Sort, Selection Sort, Linear Search, Binary Search

2 Write a Program to Implement a Linked List 3 Write a Program to Implement a Doubly Linked List 4 Write a Program to Implement a Stack Dynamically 5 Write a Program to Implement a Queue dynamically 6 Write a Program to Implement a Circular Linked List 7 Write a Program to Implement Binary Search Tree 8 Write a Program to Implement Inorder 9 Write a Program to implement Postorder 10 Write a Program to implement Preorder 11 Write a Program to implement Heapsort 12 Write a program to implement Breadth First search 13 Write a program to implement Depth First search 14 Write a Program to implement Dijkstra’s Algorithm 15 Write a Program to Implement Bubble Sort using Recursion 16 Write a Program to Implement Insertion Sort using Recursion 17 Write a Program to Implement Selection Sort using Recursion 18 Write a Program to Implement Linear Search using Recursion 19 Write a Program to Implement Linear Search using Recursion

SEMESTER III

Object Oriented programming using C++

1. Name of the Department: CSE 2. Course Name Object Oriented

programming using C++

L-3 T-0 P-2

3. Course Code 4. Type of Course (use tick mark) Core (√) PE() OE() 5. Pre-requisite (if


marks) Even () Odd () Either

Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28

Brief Syllabus: Unit I:

Introduction to C++ and Object oriented Concepts C++ Standard Library, Basics of a Typical C++ Environment, Pre-processors Directives, illustrative Simple C++ Programs. Header Files and Namespaces, library files. Introduction to Objects and Object Oriented Programming, Encapsulation (Information Hiding), Access Modifiers: Controlling access to a class, method, or variable (public, protected, private,package), Other Modifiers, Polymorphism: Overloading,Inheritance, Overriding Methods, Abstract Classes, Reusability, Class‟s Behaviors. Unit II:Classes and Data Abstraction: Introduction, Structure Definitions, Accessing Members of Structures, Class Scope and accessing Class Members, Separating Interface from Implementation, Controlling Access Function And Utility Functions, Initializing Class Objects: Constructors, Using Default Arguments With Constructors, Using Destructors, Classes : Const(Constant) Object And Const Member Functions, Object as Member of Classes, Friend Function and Friend Classes, Using This Pointer, Dynamic Memory Allocation with New and Delete, Static Class Members, Container Classes And Integrators, Proxy Classes, Function overloading. Unit III:: Operator Overloading, Inheritance, and Virtual Functions and Polymorphism: Fundamentals of Operator Overloading, Restrictions On Operators Overloading, Operator Functions as Class Members vs. as Friend Functions, Overloading, <<, >> Overloading Unary Operators, Overloading Binary Operators. Introduction to Inheritance, Base Classes And Derived Classes, Protected Members, Casting Base- Class Pointers to Derived- Class Pointers, Using Member Functions, Overriding Base – Class Members in a Derived Class, Public, Protected and Private Inheritance, Using Constructors and Destructors in derived Classes, Implicit Derived –Class Object To Base- Class Object Conversion, Composition Vs. Inheritance. Introduction to Virtual Functions, Abstract Base Classes And Concrete Classes, Polymorphism, New Classes And Dynamic Binding, Virtual Destructors, Polymorphism, Dynamic Binding. Unit IV:: Files and I/O Streams and Templates and Exception Handling: Files and Streams, Creating a Sequential Access File, Reading Data From A Sequential Access File, Updating Sequential Access Files, Random Access Files, Creating A Random Access File, Writing Data Randomly To a Random Access File, Reading Data Sequentially from a Random Access File. Stream Input/Output Classes and Objects, Stream Output, Stream Input, Unformatted I/O (with read and write), Stream Manipulators, Stream Format States, Stream Error States. Function Templates, Overloading Template Functions, Class Template, Class Templates and Non-Type Parameters, Templates and Inheritance, Templates and Friends, Templates and Static Members. Introduction, Basics of C++ Exception Handling: Try Throw, Catch, Throwing an Exception, Catching an Exception, Rethrowing an Exception, Exception specifications, Processing Unexpected Exceptions, Stack Unwinding, Constructors, Destructors and Exception Handling, Exceptions and Inheritance.

8. Learning objectives:

1. introduce the student to the concepts of C++ in computer science. 2. Acquire knowledge to make functions , Files etc

9. Course Outcomes:

a. Knowledge of programming language. b. Be aware about OOP’s concept.

c. Basic understanding on programming. 10. Unit wise detailed content Unit-1 Number of lectures

= 11 Title of the unit: Introduction to C++ and Object oriented Concepts

Introduction to C++ and Object oriented Concepts C++ Standard Library, Basics of a Typical C++ Environment, Pre-processors Directives, illustrative Simple C++ Programs. Header Files and Namespaces, library files. Introduction to Objects and Object Oriented Programming, Encapsulation (Information Hiding), Access Modifiers: Controlling access to a class, method, or variable (public, protected, private,package), Other Modifiers, Polymorphism: Overloading,Inheritance, Overriding Methods, Abstract Classes, Reusability, Class‟s Behaviors.

Unit – 2 Number of lectures

= 11 Title of the unit: Classes and Data Abstraction:

Introduction, Structure Definitions, Accessing Members of Structures, Class Scope and accessing Class Members, Separating Interface from Implementation, Controlling Access Function And Utility Functions, Initializing Class Objects: Constructors, Using Default Arguments With Constructors, Using Destructors, Classes : Const(Constant) Object And Const Member Functions, Object as Member of Classes, Friend Function and Friend Classes, Using This Pointer, Dynamic Memory Allocation with New and Delete, Static Class Members, Container Classes And Integrators, Proxy Classes, Function overloading.


= 10 Title of the unit: Operator Overloading

Operator Overloading, Inheritance, and Virtual Functions and Polymorphism: Fundamentals of Operator Overloading, Restrictions On Operators Overloading, Operator Functions as Class Members vs. as Friend Functions, Overloading, <<, >> Overloading Unary Operators, Overloading Binary Operators. Introduction to Inheritance, Base Classes And Derived Classes, Protected Members, Casting Base- Class Pointers to Derived- Class Pointers, Using Member Functions, Overriding Base – Class Members in a Derived Class, Public, Protected and Private Inheritance, Using Constructors and Destructors in derived Classes, Implicit Derived –Class Object To Base- Class Object Conversion, Composition Vs. Inheritance. Introduction to Virtual Functions, Abstract Base Classes And Concrete Classes, Polymorphism, New Classes And Dynamic Binding, Virtual Destructors, Polymorphism, Dynamic Binding.


= 10 Title of the unit: Files and I/O Streams and Templates and Exception Handling:

Files and I/O Streams and Templates and Exception Handling: Files and Streams, Creating a Sequential Access File, Reading Data From A Sequential Access File, Updating Sequential Access Files, Random Access Files, Creating A Random Access File, Writing Data Randomly To a Random Access File, Reading Data Sequentially from a Random Access File. Stream Input/Output Classes and Objects, Stream Output, Stream Input, Unformatted I/O (with read and write), Stream Manipulators, Stream Format States, Stream Error States. Function Templates, Overloading Template Functions, Class Template, Class Templates and Non-Type Parameters, Templates and Inheritance, Templates and Friends, Templates and Static Members. Introduction, Basics of C++ Exception Handling: Try Throw, Catch, Throwing an Exception, Catching an Exception, Rethrowing an Exception, Exception specifications, Processing Unexpected Exceptions, Stack Unwinding, Constructors, Destructors and Exception Handling, Exceptions and Inheritance.

11. Brief Description of self learning / E-learning component. This learning method gives students to find out their learning capability. Students involve some sort of choice in


12. Books Recommended (1 Text Books + 3-4 Reference Books) a. C++ How to Program by H M Deitel and P J Deitel, 1998, Prentice Hall b. Object Oriented Programming in Turbo C++ by Robert Lafore, 1994, The WAITE Group Press. c. Programming with C++ By D Ravichandran, 2003, T.M.H d. Object oriented Programming with C++ by E Balagurusamy, 2001, Tata McGraw-Hill e. Computing Concepts with C++ Essentials by Horstmann, 2003, John Wiley, f. The Complete Reference in C++ By Herbert Schildt, 2002, TMH


Sr. No. Title CO covered 1 nctions 2 rays 3 inters 4 is pointer 5 end Function 6 rtual Function 7 stract Class 8 heritance 9 perator Overloading 10 le Handling 11 Template 12 andling of Exceptions

SEMESTER III

Operating System

1. Name of the Department: FET 2. Course Name Operating system L T P 3. Course Code 13020317 3 0 2 4. Type of Course (use tick mark) Core (√) PE() OE() 5. Pre-requisite (if

any) Computer Architecture


Even () Odd (√)

Either Sem ()

Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical =28 8. Brief Syllabus: Unit I: Introduction Operating system and functions, Classification of Operating systems- Batch, Interactive, Time sharing, Real Time System, Multiprocessor Systems, Multiuser Systems, Multiprocess Systems, Multithreaded Systems, Operating System Structure- Layered structure, System Components, Operating System services, Reentrant Kernels, Monolithic and Microkernel Systems. Unit II: Concurrent Processes Process Concept, Principle of Concurrency, Producer / Consumer Problem, Mutual Exclusion, Critical Section Problem, Dekker’s solution, Peterson’s solution, Semaphores, Test and Set operation; Classical Problem in Concurrency- Dining Philosopher Problem, Sleeping Barber Problem; Inter Process Communication models and Schemes, Process generation. Unit III: CPU Scheduling Scheduling Concepts, Performance Criteria, Process States, Process Transition Diagram, Schedulers, Process Control Block (PCB), Process address space, Process identification information, Threads and their management, Scheduling Algorithms, Multiprocessor Scheduling. Deadlock: System model, Deadlock characterization, Prevention, Avoidance and detection, Recovery from deadlock. Unit IV: Memory Management Memory Management: Basic bare machine, Resident monitor, Multiprogramming with fixed partitions, Multiprogramming with variable partitions, Protection schemes, Paging, Segmentation, Paged segmentation, Virtual memory concepts, Demand paging, Performance of demand paging, Page replacement algorithms, Thrashing, Cache memory organization, Locality of reference. Unit V: Input/ Output I/O Management and Disk Scheduling: I/O devices, and I/O subsystems, I/O buffering, Disk storage and disk scheduling, RAID. File System: File concept, File organization and access mechanism, File directories, and File sharing, File system implementation issues, File system protection and security. 9. Learning objectives:

1. Learn fundamental operating system abstractions such as processes, threads, files, semaphores, IPC

abstractions, shared memory regions, etc., 2. Learn how the operating system abstractions can be used in the development of application programs, or to

build higher level abstractions, 3. Learn how the operating system abstractions can be implemented, 4. Learn the principles of concurrency and synchronization, and apply them to write correct concurrent

programs/software, 5. Learn basic resource management techniques (scheduling, time management, space management) and

principles and how they can be implemented. These also include issues of performance and fairness objectives, avoiding deadlocks, as well as security and protection.

10. Course Outcomes:

1. Understand and identify the System calls, protection, interrupts. 2. Understand Input/ Output, Process, disk accesses, file systems. 3. Understand the concepts of Virtual memory and how it is realized in system. 4. Implement Concurrency & synchronization Semaphores/monitors, shared memory, mutual exclusion

Process scheduling services.

11. Unit wise detailed content Unit-1 Number of

lectures = 10 Title of the unit: Introduction

Operating system and functions, Classification of Operating systems- Batch, Interactive, Time sharing, Real Time System, Multiprocessor Systems, Multiuser Systems, Multiprocess Systems, Multithreaded Systems, Operating System Structure- Layered structure, System Components, Operating System services, Reentrant Kernels, Monolithic and Microkernel Systems. Unit - 2 Number of

lectures = 10 Title of the unit: Concurrent Processes

Process Concept, Principle of Concurrency, Producer / Consumer Problem, Mutual Exclusion, Critical Section Problem, Dekker’s solution, Peterson’s solution, Semaphores, Test and Set operation; Classical Problem in Concurrency- Dining Philosopher Problem, Sleeping Barber Problem; Inter Process Communication models and Schemes, Process generation. Unit - 3 Number of

lectures = 7 Title of the unit: CPU Scheduling

Scheduling Concepts, Performance Criteria, Process States, Process Transition Diagram, Schedulers, Process Control Block (PCB), Process address space, Process identification information, Threads and their management, Scheduling Algorithms, Multiprocessor Scheduling. Deadlock: System model, Deadlock characterization, Prevention, Avoidance and detection, Recovery from deadlock. Unit - 4 Number of

lectures = 8 Title of the unit: Memory Management

Memory Management: Basic bare machine, Resident monitor, Multiprogramming with fixed partitions, Multiprogramming with variable partitions, Protection schemes, Paging, Segmentation, Paged segmentation, Virtual memory concepts, Demand paging, Performance of demand paging, Page replacement algorithms, Thrashing, Cache memory organization, Locality of reference. Unit - 5 Number of

lectures = 7 Title of the unit: Input/ Output

I/O Management and Disk Scheduling: I/O devices, and I/O subsystems, I/O buffering, Disk storage and disk scheduling, RAID. File System: File concept, File organization and access mechanism, File directories, and File sharing, File system implementation issues, File system protection and security. 12. Brief Description of self learning / E-learning component. This learning method gives students to find out their learning capability. Students involve some sort of choice

in this learning. As self directed learning learners can determine which modules or scenarios to review again and again.

13. Books Recommended (2 Text Books + 2 Reference Books)

1. Operating Systems Concepts - Silberschatz, Galvin and Gagne,Wiley Publications 2. Operating Systems: A Concept based Approach - D M Dhamdhere, 2nd Edition. 3. Operating Systems - Sibsankar Halder and Alex A Aravind, Pearson Education. 4. An Introduction to Operating System - Harvey M Dietel, Pearson Education

Lab Components

Sr. No. Title CO covered 1. Install Linux 2. Various basic commands of LINUX 3. Internal Commands 4. External Commands 5. Comparison of various OS. 6. Managing users and groups in LINUX 7. CPU scheduling algorithms. 8. Shell script to find the factorial value of any number entered through

the keyboard.

9. Study various shell commands in LINUX.

SEMESTER III

Digital Electronics

1. Name of the Department Computer Science and Engineering 2. Course Name Digital Electronics L T P 3. Course Code 3 0 2 4. Type of Course (use tick mark)

COURSE Core (√) PE() OE()

5. Pre-requisite (if any)

Physics 6. Frequency (use tick marks)

Even () Odd (√) Either Sem()

EverySem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28 8. Learning objectives:

i) Understanding the different number systems used in computerized system and codes used to represent the digits and fundamental of arithmetic operation using each number system and codes.

ii) Understanding the minimization of logic expression and designing combinational and sequential digital circuits

iii) Analyzing the operation and design constraints of CMOS and TTL circuit for logic fabrication. iv) Enabling students to take up application specific sequential circuit to specify the finite state machine and

designing the logic circuit. 9. Course Outcomes:On completion of this course, the students will be able to

i) Verify and analyze the input/output data of each logic gate and circuits such as adders, counters, coders, etc. ii) Analyze the basic operation of memory cell and its limitations in circuit designing. iii) Apply the digital circuit design concept in developing basic component of computer organization, projects or

experiments.


= 9 Title of the unit:Number System and Boolean Algebra

Review of number system; types and conversion, codes. Boolean algebra: De-Morgan’s theorem, switching functions, Prime Implicants and Essential Prime Implicants definition and simplification using K-maps upto 5 variables & Quine McCluskey method. Unit - 2 Number of lectures

= 9 Title of the unit:Combinational Circuits

Introduction to Logic Gates: AND, OR, NOT, NAND, NOR, EX-OR, EX-NOR and their combinations. Design of adder, subtractors, comparators, code converters, encoders, decoders, multiplexers and de-multiplexers, Function realization using gates & multiplexers Unit - 3 Number of lectures

= 8 Title of the unit:Synchronous Sequential Circuits

Introduction to Latches and Flip flops – SR, D, JK and T. Design of synchronous sequential circuits – Counters, shift registers. Finite State Machine Design, Mealy, Moore Machines, Analysis of synchronous sequential circuits;, state diagram; state reduction; state assignment with examples. Unit - 4 Number of lectures

= 8 Title of the unit:Asynchronous Sequential Circuits

Analysis of asynchronous sequential machines, state assignment, asynchronous design problem Unit - 5 Number of lectures

= 8 Title of the unit:PLD, Memories and Logic Families

Memories: ROM,RAM, PROM, EPROM, Cache Memories, PLA, PLD, FPGA, digital logic families: TTL, ECL, CMOS. 11. Brief Description of self learning / E-learning component

The purpose of the course is to teach principles of digital electronics. The material covers a variety of topics including Boolean algebra, basic gates, logic circuits, flip-flops, registers, arithmetic circuits, counters, interfacing with analog devices, and computer memory. The basics gates can be learned by ICs available for each gate. Combinational and sequential circuits can be learned by experiment kits. Sequential circuits includes the detailed study of counters and finite state machines. 12. Books Recommended (3 Text Books + 2-3 Reference Books)

i) Mano, Morris. “Digital logic.” Computer Design. Englewood Cliffs Prentice-Hall (1979).

ii) Kumar, A. Anand. Fundamentals Of Digital Circuits 2Nd Ed. PHI Learning Pvt. Ltd., 2009.

iii) Taub, Herbert, and Donald L. Schilling. Digital integrated electronics. New York: McGraw-Hill, 1977.

iv) Floyd, Thomas L. Digital Fundamentals, 10/e. Pearson Education India, 1986.

v) Malvino, Albert Paul, and Donald P. Leach. Digital principles and applications. McGraw-Hill, Inc., 1986.

vi) Jain, Rajendra Prasad. Modern Digital Electronics 3e. Tata McGraw-Hill Education, 2003.

13. Lab components

Sr. No. Title CO covered 1 Logic gates trainer kit 2 Flip flop trainer kit 3 Multiplexer and demultiplexer kit 4 To verify the function of up-down counter

SEMESTER III

Discrete Mathematics

1. Name of the Department: CSE 2. Course Name Discrete Mathematics L T P 3. Course Code 13020419 3 0 0 4. Type of Course (use tick mark) Core ( ) PE(√) OE() 5. Pre-requisite (if

any) Fundamental of Mathematics


Even () Odd (√) Either Sem ()

Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus: Syllabus cover set theory & partial order set, Algebric structures, Propositional logic etc. 9. Learning objectives:

1. Develop a foundation of set theory concepts and notation 2. Explore a variety of various mathematical structures by focusing on mathematical objects,

operations, and resulting properties 3. Develop formal logical reasoning techniques and notation 4. Demonstrate the application of logic to analyzing and writing proofs 5. Develop techniques for counting, permutations and combinations 6. Develop the concept of relation through various representations (digraphs, matrices, lists).

10. Course Outcomes: 1. Construct proofs using direct proof, proof by contraposition, proof by contradiction, proof by cases 2. Construct mathematical arguments using logical connectives and quantifiers and verify the correctness of an

argument using propositional and predicate logic and truth tables. 3. Demonstrate the ability to solve problems using counting techniques and combinatory in the context of discrete

probability. 4. Solve problems involving recurrence relations and generating functions.

11. Unit wise detailed content Unit-1 Number of lectures = 10 Set Theory& Partial order sets Introduction, Combination of sets, Multisets, Ordered pairs. Proofs of some general identities on sets. Relations: Definition, Operations on relations, Properties of relations, Composite Relations, Equality of relations, Recursive definition of relation, Order of relations. Functions: Definition, Classification of functions, Operations on functions, Recursively defined functions, Growth of Functions, Natural Numbers: Introduction, Mathematical Induction, Variants of Induction, Induction with Nonzero Base cases. Proof Methods, Proof by counter – example, Proof by contradiction.Definition, Partial order sets, Combination of partial order sets, Hasse diagram. Lattices: Definition, Properties of lattices – Bounded, Complemented, Modular and Complete lattice. Unit – 2 Number of lectures = 8 Algebraic Structures Definition, Groups, Subgroups and order, Cyclic Groups, Cosets, Lagrange’s theorem, Normal Subgroups, Permutation and Symmetric groups, Group Homomorphisms, Definition and elementary properties of Rings and Fields, Integers Modulo n. Unit – 3 Number of lectures = 8 Propositional Logic Proposition, well-formed formula, Truth tables, Tautology, Satisfiability, Contradiction, Algebra of proposition, Theory of Inference Predicate Logic: First order predicate, well-formed formula of predicate, quantifiers, Inference theory of predicate logic. Unit – 4 Number of lectures = 8 Graph Theory Definition, Binary tree, Binary tree traversal, Binary search tree. Graphs: Definition and terminology, Representation of graphs, Multigraphs, Bipartite graphs, Planar graphs, Isomorphism and Homeomorphism of graphs, Euler and Hamiltonian paths, Graph coloring. Unit – 5 Number of lectures = 8 Recurrence Relation & Generating function Recursive definition of functions, Recursive algorithms, Method of solving recurrences. Combinatory, Introduction, Counting Techniques, Pigeonhole Principle. 12. Brief Description of self learning / E-learning component. This learning method gives students to find out their learning capability. Students involve some sort of choice in this learning. As self directed learning learners can determine which modules or scenarios to review again and again.

13. Books Recommended (2 Text Books + 2 Reference Books) 1. Elements of Distcrete Mathematics - Liu and Mohapatra, McGraw Hill Publications 2. Discrete Mathematical Structures - B. Kolman, R.C. Busby, and S.C. Ross, PHI Publications 3. Discrete Mathematical Structures with Application to Computer Science - Jean Paul Trembley and R Manohar,

McGraw-Hill Publications 4. Discrete and Combinatorial Mathematics - R.P. Grimaldi, Addison Wesley 5. Discrete Mathematics and Its Applications - Kenneth H. Rosen, McGraw-Hill

B.Tech-Computer Science & Engineering SEMESTER IV

Aptitude Building

1. Name of the Department – CENTRE FOR LANGUAGES AND COMMUNICATION 2. Course Name Aptitude Building L - 2 T – 0 P -2 3. Course Code 13020401 4. Type of Course (use tick mark) Core (√) PE() OE() 5. Pre-requisite (if

any) Proficiency in English


Even (√)

Odd () Either Sem ()

Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 28 Tutorials = 0 Practical = 28 8. Brief Syllabus Unit-I Report, Proposal, and Project: Introduction to Academic writing: Report Writing, Types, Structure, Style and Writing of Reports (on different topics), Characteristics of Report, Categories and Types of Report, Types of Proposal, Nature and Significance, Structure of formal Proposal, Sample Proposal, Writing Proposals on different topics, Difference between Report and Proposal, Project Writing: Essential Features, Structure, Choosing the Subject and Writing the Project on the related Subject. Unit-II: Speaking Skills: Spontaneous and structured introduction, Discussion on current scenarios in society, Panel Discussion, Fish bowl technique, Group Discussions, Public Speaking, Assertive and Negotiation Strategies. Unit-III: Communication Skills: Introduction to various levels of designations in an organization, Discussion of the work flow in an organization, Jest of working culture in different organization, Activities related to Skills required for Engineers (Managerial Skills, Leadership Skills, and Organizational Skills). Unit-IV: Strategies for Recruitment: Introduction to Virtual online interviews and selection process, Recruitments and Interviews, Stages in Job Interview, Desirable Qualities, Reviewing the common Question Types of Interviews. Unit-V: Numbers and Arithmetic Basic: Classification of Numbers, Divisibility rules –LCM/HCF, Remainders – Base System, Surds, Indices, Logarithms, Percentage, Profit and Loss, Ratio and Proportion, Approximations, Vedic Maths, Intro to DI, Comprehensive Practice Test on Number system, Percentage and Calculation, Simple Arithmetic: Code-decoding, Analogies, Direction Test, Blood relations ,Comprehension Practice test-1 (Cumulative) ,Comprehension Practice test-2 (Cumulative) 9. Learning objectives: 1 To prepare the students write their project report 2. Get ready to write proposals implementing their ideas 3. To prepare them to speak in Public 4. To make them prepare effective Presentations 5. Enable students in Aptitude building 6. Enable students to use their Aptitude Knowledge effectively in decision making 10. Course Outcomes (COs):

6. Able to write the proposals and assigned projects 7. Confident in Public Speaking 8. Can write Presentations on different Industrial topics 9. Improve arithmetic aptitude 10. Learn tricks to solve Aptitude questions faster thereby saving time during competitive exams


= 4 Number of

Title of the unit: Unit-I Report, Proposal, and Project

Practical = 4 Unit-I Report, Proposal, and Project: Introduction to Academic writing: Report Writing, Types, Structure, Style and Writing of Reports (on different topics), Characteristics of Report, Categories and Types of Report, Types of Proposal, Nature and Significance, Structure of formal Proposal, Sample Proposal, Writing Proposals on different topics, Difference between Report and Proposal, Project Writing: Essential Features, Structure, Choosing the Subject and Writing the Project on the related Subject. Unit – 2 Number of lectures

= 4 Number of Practical = 4

Title of the unit: Speaking Skills

Unit-II: Speaking Skills: Spontaneous and structured introduction, Discussion on current scenarios in society, Panel Discussion, Fish bowl technique, Group Discussions, Public Speaking, Assertive and Negotiation Strategies. Unit – 3 Number of lectures

= 4 Title of the unit: Communication Skills

Unit-III: Communication Skills: Introduction to various levels of designations in an organization, Discussion of the work flow in an organization, Jest of working culture in different organization, Activities related to Skills required for Engineers (Managerial Skills, Leadership Skills, and Organizational Skills). Unit – 4 Number of lectures

= 4 Title of the unit: Strategies for Recruitment

Unit-IV: Strategies for Recruitment: Introduction to Virtual online interviews and selection process, Recruitments and Interviews, Stages in Job Interview, Desirable Qualities, Reviewing the common Question Types of Interviews. Unit – 5 Number of lectures

= 4 Title of the unit: Numbers and Arithmetic Basic:

Unit-V: Numbers and Arithmetic Basic: Classification of Numbers, Divisibility rules –LCM/HCF, Remainders – Base System, Surds, Indices, Logarithms, Percentage, Profit and Loss, Ratio and Proportion, Approximations, Vedic Maths, Intro to DI, Comprehensive Practice Test on Number system, Percentage and Calculation, Simple Arithmetic: Code-decoding, Analogies, Direction Test, Blood relations ,Comprehension Practice test-1 (Cumulative) ,Comprehension Practice test-2 (Cumulative) 12. Brief Description of self learning / E-learning component Students can practice from various sites online for Aptitude Building Questions. https://www.indiabix.com/, https://www.indiabix.com/online-test/aptitude-test , https://www.crazyengineers.com › ... › Engineering Jobs & Career Advice, https://testbook.com/aptitude etc. The students will be encouraged to learn using the SGT ELearning portal and choose the relevant lectures delivered by subject experts of SGT University.

The link to the E-Learning portal: https://elearning.sgtuniversity.ac.in/course-category/general/

13. Books Recommended (3 Text Books + 2-3 Reference Books) 1. Sanjay Kumar and Pushp Lata ‘Communication Skills’, Oxford University Press 2012 2. Raymond Murphy ‘Essential English Grammar’, Cambridge University Press 1998 3. Meenakshi Raman and Sangeeta Sharma ‘Technical Communication Principles and Practice’, Oxford University

Press 2012 4. R. K. Narayan, Malgudi Days: A Collection of Short Stories, Penguin 2006

5. Meenakshi Raman and Prakash ‘Business Communication’ Oxford University Press 2011 14. Tutorial / Extended Tutorial /presentation/Case study components

Sr. No. Title

1 Extensive writing skills

https://www.indiabix.com/

https://www.indiabix.com/online-test/aptitude-test

https://testbook.com/aptitude


2 Polished Public Speaking Skills and Negotiation Strategies

3 Sharp Knowledge of various Organizational Skills

4 Building Knowledge on Interviews and Selection Process

5 Solving Different Arithmetic Equations


Sr. No. Title

1 Technical Writing Practices

3 Group Discussions

4 Activities to enhance Organizational skills

5 Activities related to Interviews, online interview practices

6 Solving Online Aptitude Questions

SEMESTER IV

Computer graphics

1. Name of the Department: FET 2. Course Name Computer Graphics L-3 T-0 P-2 3. Course Code 13020410 4. Type of Course (use tick mark) Core (√) PE() OE() 5. Pre-requisite (if

any) C Language 6. Frequency (use tick

marks) Even (√)

Odd () Either Sem()

EverySem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28 8. Brief Syllabus: Introduction to Computer Graphics and Line Generation and Circle Generation, 2-D viewing Pipeline, 2-D and 3-D Transformations, their Matrix representations,Curves and Surfaces, Detection and removal of Hidden lines and Surfaces, Illumination and Shading. 9. Learning objectives:

To provide a comprehensive introduction to computer graphics leading to the ability to understand contemporary terminology, progress, issues, and trends. To understand computer graphics techniques (2-D/3-D), focusing on 3D modelling, image synthesis, and rendering. Introduce geometric transformations, geometric algorithms, software systems (OpenGL), 3D object models (surface, volume and implicit), visible surface algorithms, image synthesis, shading and mapping, ray tracing, radiosity, global illumination, photon mapping, and anti-aliasing. To explore the interdisciplinary nature of computer graphics which is emphasized in the wide variety of examples and applications 10. Course Outcomes:

i. To develop a facility with the relevant mathematics of computer graphics ii. Apply principles and techniques of computer graphics, e.g., the graphics pipeline, and Bresenham’s algorithm for speedy line and circle generation.

iii. Apply computer graphics concepts in the development of computer games, information visualization, and business applications


= 12 Title of the unit:Introduction and Line Generation

Types of computer graphics, Graphic Displays- Random scan displays, Raster scan displays, Frame buffer and video controller, Points and lines, Line drawing algorithms, Circle generating algorithms, Midpoint circle generating algorithm, and parallel version of these algorithms. Unit - 2 Number of lectures

= 11 Title of the unit:Transformations

Basic transformation, Matrix representations and homogenous coordinates, Composite transformations, Reflections and shearing. Windowing and Clipping: Viewing pipeline, Viewing transformations, 2-D Clipping algorithms-Line clipping algorithms such as Cohen Sutherland line clipping algorithm, Liang Barsky algorithm, Line clipping against nonrectangular clip windows; Polygon clipping – Sutherland Hodgeman polygon clipping, Weiler and Atherton polygon clipping, Curve clipping, Text clipping. Unit - 3 Number of lectures

= 6 Title of the unit:Three Dimensional

3-D geometric primitives, 3-D Object representation, 3-D Transformation, 3-D viewing, projections, 3-D Clipping. Unit - 4 Number of lectures

= 6 Title of the unit:Curves and Surfaces

Quadric surfaces, Spheres, Ellipsoid, Blobby objects, introductory concepts of Spline, Bspline and Bezier curves and surfaces. Unit - 5 Number of lectures

= 7 Title of the unit: Hidden Lines and Surfaces

Back Face Detection algorithm, Depth buffer method, A- buffer method, Scan line method, basic illumination models – Ambient light, Diffuse reflection, Specular reflection and Phong model, Combined approach, Warn model, Intensity Attenuation, Color consideration, Transparency and Shadows.

12. Brief Description of self learning / E-learning component. Online Video Lectures available 13. Books Recommended (3 Text Books + 2-3 Reference Books) i) Computer Graphics C Version - Donald Hearn and M Pauline Baker, Pearson Education ii) Computer Graphics - Amrendra N Sinha and Arun D Udai, TMH Publications iii) Computer Graphics: A Programming Approach - Steven Harrington, TMH Publications iv) Procedural Elements of Computer Graphics - Rogers, McGraw Hill


Sr. No. Title 1 Introduction and Line Generation 2 Transformations 3 Three Dimensional 4 Curves and Surfaces 5 Hidden Lines and Surfaces 15. Lab component components

Sr. No. Title 1 Line Drawing Algorithms 2 Circle Drawing Algorithms 3 Ellipse Drawing Algorithms 4 Polygon Filling Algorithms 5 Basic Transformations 6 Composite Transformations 7 Line Clipping Algorithms 8 Polygon Clipping Algorithms 9 Curve Generations 10 Animation

SEMESTER IV

Computer Architecture and Organization

1. Name of the Department: FET 2. Course Name CAO L-3 T-0 P-0 3. Course Code 4. Type of Course (use tick mark) Core (√) PE() OE() 5. Pre-requisite (if



Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus: Introduction to organizational Basic building block diagram of a digital computer system. As the

course progresses each major block ranging from Processor to I/O will be discussed in their full architectural detail. The course talks primarily about Computer Organization and Architecture issues, Architecture of a typical Processor, Memory Organization, I/O devices and their interface and System Bus organization etc.

9. Learning objectives: Provide the skills needed for building computer system for various applications in a career in Computer Science field. 10. Course Outcomes:

1) To understand the basic knowledge of Computer system and its component and functioning of each components. 2) To understand and analyze computer architecture and organization, computer arithmetic, and CPU design. 3) To understand I/O system and interconnection structures of computer system. 4) To understand and analyze I/O techniques and functioning of memory. 5) To understand various types of buses in a computer system and illustrate how data transfers is performed.


= 9 Title of the unit: Basic structure of computers

Functional Modules - Basic operational concepts - Bus structures - Software performance – Memory locations and addresses – Memory operations – Instruction and instruction sequencing – Addressing modes – Assembly language – Basic I/O operations– Stacks and queues. Unit – 2 Number of lectures

= 9 Title of the unit: Arithmetic Module

Addition and subtraction of signed numbers – Design of fast adders – Multiplication of positive numbers - Signed operand multi-plication and fast multiplication – Integer division – Floating point numbers and operations. Unit – 3 Number of lectures

= 8 Title of the unit: Basic processing Module

Fundamental concepts – Execution of a complete instruction – Multiple bus organization – Hardwired control – Micro programmed control - Pipelining – Basic concepts – Data hazards – Instruction hazards – Influence on Instruction sets – Data path and control consideration – Superscalar operation. Unit – 4 Number of lectures

= 8 Title of the unit: Memory System

Basic concepts – Semiconductor RAMs - ROMs – Speed - size and cost – Cache memories - Performance consideration – Virtual memory- Memory Management requirements – Secondary storage. Unit – 5 Number of lectures

= 8 Title of the unit: PLD, Memories and Logic Families

Accessing I/O devices – Interrupts – Direct Memory Access – Buses – Interface circuits – Standard I/O Interfaces (PCI, SCSI, USB). 12. Brief Description of self learning / E-learning component. This learning method gives students to find out their learning capability. Students involve some sort of choice in


13. Books Recommended (1 Text Books + 3-4 Reference Books) v) Computer Organization - Carl Hamacher, Zvonko Vranesic and Safwat Zaky, 5th Edition, McGraw- Hill, 2002. vi) Computer Organization and Architecture – Designing for Performance - William Stallings, Pearson Education,

2003.

vii) Computer Organisation and Design - Patterson, Elsevier Pub. 2009 viii) Computer Organization and Design: The hardware / software interface - David A.Patterson and John

L.Hennessy, Morgan Kaufmann, 2002. ix) Computer Architecture and Organization - John P.Hayes, McGraw Hill, 1998.

SEMESTER IV


1. Name of the Department 2. Course Name Database

Management System

L T P

3. Course Code 3 0 2 4. Type of Course (use tick mark) Core (√ ) PE() OE() 5. Pre-requisite (if


marks) Even (√)


Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28 8. Brief Syllabus COURSE CONTENT Unit I: Introduction An overview of database management system, database system vs file system, Database system concept and architecture, data model schema and instances, data independence and database language and interfaces, data definitions language, DML, Overall Database Structure. Data modeling using the Entity Relationship Model: ER model concepts, notation for ER diagram, mapping constraints, keys, Concepts of Super Key, candidate key, primary key, Generalization, aggregation, reduction of an ER diagrams to tables, extended ER model, relationship of higher degree. Unit II: Relational data Model and Language Relational data model concepts, integrity constraints, entity integrity, referential integrity, Keys constraints, Domain constraints, relational algebra, relational calculus, tuple and domain calculus. Introduction on SQL: Characteristics of SQL, advantage of SQL. SQL data type and literals. Types of SQL commands. SQL operators and their procedure. Tables, views and indexes. Queries and sub queries. Aggregate functions. Insert, update and delete operations, Joins, Unions, Intersection, Minus, Cursors, Triggers, Procedures in SQL/PL SQL. Unit III: Data Base Design & Normalization Functional dependencies, normal forms, first, second, third normal forms, BCNF, inclusion dependence, loss less join decompositions, normalization using FD, MVD, and JDs, alternative approaches to database design. Unit IV: Transaction Processing Concept Transaction system, Testing of serializability, serializability of schedules, conflict & view serializable schedule, recoverability, Recovery from transaction failures, log based recovery, checkpoints, deadlock handling. Distributed Database: distributed data storage, concurrency control, directory system. Unit V: Concurrency Control Techniques Concurrency control, Locking Techniques for concurrency control, Time stamping protocols for concurrency control, validation based protocol, multiple granularity, Multi version schemes, Recovery with concurrent transaction, case study of Oracle/DB2. 9. Learning objectives:

(i) Knowledge of DBMS, in terms of use and implementations. (ii) Experience with analysis and design of various database softwares (SQL/PL-SQL, Forms, Reports, DBA, DBM)

in order to manage a large complex database systems. (iii) Understand the concept of data planning and database design for serving different types of users with varying

skill levels. (iv) Handling different user views of the same stored data, combining interrelated data setting standards, controlling

concur-rent updates so as to maintain data integrity. (v) Managing, planning and coordinating restart and recovery operations across multiple users for a large complex

systems. 10. Course Outcomes:

(i) Understand the relational database theory, and be able to write relational algebra expressions for queries, logical

design of databases, including the E‐R method and normalization approach. (ii) Illustrate commercial relational database system by writing SQL (iii) Understand the relational database theory, and be able to write relational algebra expressions for queries, logical

design of databases, including the E-R method and normalization approach.

(iv) Understand and analyze the database storage structures and access techniques like file and page organizations, indexing methods including B‐tree, hashing, query evaluation techniques and and query optimization.

(v) Understand various issues of transaction processing and concurrency control by designing and development of a database application system as part of a team.


= 10 Title of the unit: Introduction

An overview of database management system, database system vs file system, Database system concept and architecture, data model schema and instances, data independence and database language and interfaces, data definitions language, DML, Overall Database Structure. Data modeling using the Entity Relationship Model: ER model concepts, notation for ER diagram, mapping constraints, keys, Concepts of Super Key, candidate key, primary key, Generalization, aggregation, reduction of an ER diagrams to tables, extended ER model, relationship of higher degree. Unit - 2 Number of lectures

= 8 Title of the unit: Relational data Model and Language

Relational data model concepts, integrity constraints, entity integrity, referential integrity, Keys constraints, Domain constraints, relational algebra, relational calculus, tuple and domain calculus. Introduction on SQL: Characteristics of SQL, advantage of SQL. SQL data type and literals. Types of SQL commands. SQL operators and their procedure. Tables, views and indexes. Queries and sub queries. Aggregate functions. Insert, update and delete operations, Joins, Unions, Intersection, Minus, Cursors, Triggers, and Procedures in SQL/PL SQL. Unit - 3 Number of lectures

= 8 Title of the unit: Data Base Design & Normalization

Functional dependencies, normal forms, first, second, third normal forms, BCNF, inclusion dependence, loss less join decompositions, normalization using FD, MVD, and JDs, alternative approaches to database design. Unit - 4 Number of lectures

= 8 Title of the unit: Transaction Processing Concept

Transaction system, Testing of serializability, serializability of schedules, conflict & view serializable schedule, recoverability, Recovery from transaction failures, log based recovery, checkpoints, deadlock handling. Distributed Database: distributed data storage, concurrency control, directory system. Unit - 5 Number of lectures

= 8 Title of the unit: Concurrency Control Techniques

Concurrency control, Locking Techniques for concurrency control, Time stamping protocols for concurrency control, validation based protocol, multiple granularity, Multi version schemes, Recovery with concurrent transaction, case study of Oracle/DB2. 12. Brief Description of self learning / E-learning component Online Video Lectures on Data Base Management System. Practice of E-R Diagrams on various Real Time Systems such as Library Management System, Airline and Railway Reservation System, Payroll System, Inventory Management System. ebooks available online:- pages.cs.wisc.edu/~dbbook/openAccess/thirdEdition/solutions/ans3ed-oddonly.pdf Online tutorials and pdf files :- www.kciti.edu/wp-content/uploads/2017/07/dbms_tutorial.pdf 13. Books Recommended (3 Text Books + 2-3 Reference Books) x) Fundamentals of Database Systems – Elmasri and Navathe, Addision Wesley xi) An Introduction to Database Systems - Date C J, Addision Wesley xii) Database Concepts - Korth, Silbertz and Sudarshan, McGraw Hill xiii) An Introduction to Database Systems - Bipin C. Desai, Galgotia Publications xiv) Database Management System - Majumdar and Bhattacharya, TMH xv) Database Management System – Ramkrishnan and Gehrke, McGraw Hill

Tutorial / Extended Tutorial /presentation/Case study components

Sr. No. Title CO covered 1 Data Definition and Manipulation language

2 Entity Relationship Model: ER model concepts 3 Query Processing and Optimization 4 Concurrency Control Techniques 5 Normalization in Practical

Lab component components

Sr. No. Title CO covered 1 DDL Queries 2 Use of Comparison Operators 3 Use of Logical Operators 4 Use of SQL Operators 5 Relational Algebra Queries 6 Joining Tables and implementing Queries 7 Use of Sub Queries & Nested Queries 8 Writing Pl/SQL Programs 9 Use of ROLL BACK, COMMIT & CHECK POINTS 10 Creating VIEWS, CURSORS and TRGGERS & writing ASSERTIONS 11 Create FORMS and REPORTS

SEMESTER IV

Computer Networks

1. Name of the Department 2. Course Name Computer

Networks L T P

3. Course Code 3 0 2 4. Type of Course (use tick mark) Core (√ ) PE() OE() 5. Pre-requisite (if


marks) Even (√)


Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28 8. Brief Syllabus COURSE CONTENT Unit I: Introduction Concepts Goals and Applications of Networks, Network structure and architecture, The OSI reference model, services, Network Topology Design - Delay Analysis, Back Bone Design, Local Access Network Design, Physical Layer Transmission Media, Switching methods, ISDN, Terminal Handling. Unit II: Medium Access sub layer Medium Access sub layer - Channel Allocations, LAN protocols -ALOHA protocols - Overview of IEEE standards - FDDI. Data Link Layer - Elementary Data Link Protocols, Sliding Window protocols, Error Handling. Unit III: Network Layer Network Layer - Point - to Pont Networks, routing, Congestion control Internetworking -TCP / IP, IP packet, IP address, IPv6. Unit IV: Transport Layer Transport Layer - Design issues, connection management, session Layer-Design issues, remote procedure call. Presentation Layer-Design issues, Data compression techniques, cryptography - TCP - Window Management. Unit V: Application Layer File Transfer, Access and Management, Electronic mail, Virtual Terminals, Other application. Example Networks- Internet and Public Networks. 9. Learning objectives:

1. Discuss the evolution of computer network concepts. 2. Understand the structure of computer networks, factors affecting computer network deployment. 3. Describe emerging technology in the net-centric computing area and assess their current

capabilities, limitations and potential applications. 4. Program and analyse network protocols, architecture, algorithms and other safety critical issues in real-life

scenario. 10. Course Outcomes:

1. Examine and analyze various protocols like transport-layer concepts: Transport-Layer services -Reliable vs. un-

reliable data transfer -TCP protocol -UDP protocol 2. Examine and analyze the network-layer concepts like Network-Layer services –Routing -IP protocol -IP

addressing 3. Examine and analyze the different link-layer and local area network concepts like Link-Layer services –Ethernet

-Token Ring -Error detection and correction -ARP protocol 4. Analyze and implement application of network system.


= 10 Title of the unit: Introduction Concepts

Goals and Applications of Networks, Network structure and architecture, The OSI reference model, services, Network Topology Design - Delay Analysis, Back Bone Design, Local Access Network Design, Physical Layer Transmission Media, Switching methods, ISDN, Terminal Handling.


Title of the unit: Medium Access sub layer

Medium Access sub layer - Channel Allocations, LAN protocols -ALOHA protocols - Overview of IEEE standards - FDDI. Data Link Layer - Elementary Data Link Protocols, Sliding Window protocols, Error Handling. Unit - 3 Number of lectures

= 8 Title of the unit: Network Layer

Network Layer - Point - to Pont Networks, routing, Congestion control Internetworking -TCP / IP, IP packet, IP address, IPv6. Unit - 4 Number of lectures

= 8 Title of the unit: Transport Layer

Transport Layer - Design issues, connection management, session Layer-Design issues, remote procedure call. Presentation Layer-Design issues, Data compression techniques, cryptography - TCP - Window Management. Unit - 5 Number of lectures

= 8 Title of the unit: Application Layer

File Transfer, Access and Management, Electronic mail, Virtual Terminals, Other application. Example Networks- Internet and Public Networks. 12. Brief Description of self learning / E-learning component Online Video Lectures on computer networks Practice of networking algorithims 13. Books Recommended (1Text Books + 4 Reference Books)

i. Forouzen, “Data Communication and Networking”, TMH

ii. A.S. Tanenbaum, Computer Networks, Pearson Education

iii. W. Stallings, Data and Computer Communication, Macmillan Press

iv. Anuranjan Misra, “Computer Networks”, Acme Learning

v. G. Shanmugarathinam, ”Essential of TCP/ IP”, Firewall Media

Tutorial Extended Tutorial /presentation/Case study components

Sr. No. Title CO covered 1 Introduction Concepts (ii) 2 Medium Access sub layer (iii) 3 Network Layer (ii) 4 Transport Layer (iii) 5 Application Layer (iv)

Lab components

Sr. No. Title CO covered 1 Introduction to basic Linux networking commands. (Commands like ipconfig, getmac,

tracert, pathping, arp, ping, netstat, finger etc.) (i)

2 Implement bit stuffing and de-stuffing (ii) 3 Write a program for hamming code generation for error detection and correction. (iii) 4 Implement cyclic redundancy check (CRC). (iv) 5 Write a program for congestion control using the leaky bucket algorithm. (v) 6 Implement Dijkstra’s algorithm to compute a shortest path through graph. (vi) 7 Take a 64-bit plain text and encrypt the same using DES algorithm. (vii) 8 Using RSA algorithm encrypts a text data and decrypts the same. (viii) 9 Implementation of the link state routing protocols. (ix) 10 Implementation of LZW compression and decompression algorithms. (x) 11 Introduction to basic Linux networking commands. (Commands like ipconfig, getmac,

tracert, pathping, arp, ping, netstat, finger etc.) (xi)

SEMESTER IV

Theory of Automata & Formal Language

1. Name of the Department : Computer Science Engineering 2. Course Name Theory of

Automata & Formal Language

L T P

3. Course Code 3 0 0 4. Type of Course (use tick mark) Core PE() OE() 5. Pre-requisite (if

any) ADA 6. Frequency (use

tick marks) Even Odd Either

Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus This course introduces some fundamental concepts in automata theory and formal languages including grammar, finite automaton, regular expression, formal language, pushdown automaton and Turing machine. This subject not only forms the basic models of computation, it also includes the foundation of many branches of computer science, e.g. compilers, software engineering, concurrent systems, etc. The properties of these models will be studied and various rigorous techniques for analyzing and comparing them will be discussed, by using both formalism and examples. 9. Learning objectives: The objective of this course is to

1. Introduce the student to the concepts of theory of computation in computer science. 2. Acquire insights into the relationship among formal languages, formal grammars, and automata. 3. learn to design automats and Turing machine

10. Course Outcomes: On completion of this course, the students will be able to:-

i. Understand the importance of automata as a modelling tool of computational problems ii. Understand the role of context-free languages and their limitations

iii. Understand the basis of theory of computation, in particular the role of key problems in defining classes of equivalent problems from a computational perspective

iv. Understand the limitations of computational procedures 11. Unit wise detailed content Unit-1 Number of

lectures = 8 Title of the unit: Introduction

Alphabets, Strings and Languages; Automata and Grammars, Deterministic finite Automata (DFA)-Formal Definition, Simplified notation: State transition graph, Transition table, Language of DFA, Nondeterministic finite Automata (NFA), NFA with epsilon transit ion, Language of NFA, Equivalence of NFA and DFA, Minimization of Finite Automata, Distinguishing one string from other, Myhill-Nerode Theorem Unit - 2 Number of

lectures = 8 Title of the unit: Regular expression (RE)

Regular expression (RE) Definition, Operators of regular expression and their precedence, Algebraic laws for Regular expressions, Kleen’s Theorem, Regular expression to FA, DFA to 39 Regular expression, Arden Theorem, Non Regular Languages, Pumping Lemma for regular Languages . Application of Pumping Lemma, Closure properties of Regular Languages, Decision properties of Regular Languages, FA with output: Moore and Mealy machine, Equivalence of Moore and Mealy Machine, Applications and Limitation of FA Unit - 3 Number of

lectures = 10 Title of the unit: Context free grammar (CFG) & Context Free Languages CFL)

Definition, Examples, Derivation, Derivation trees, Ambiguity in Grammer, Inherent ambiguity, Ambiguous to Unambiguous CFG, Useless symbols, Simplification of CFGs, Normal forms for CFGs: CNF and GNF, Closure proper ties of CFLs, Decision Properties of CFLs: Emptiness, Finiteness and Membership, Pumping lemma for CFLs. Unit - 4 Number of Title of the unit: Push Down Automata (PDA)

lectures = 8 Description and definition, Instantaneous Description, Language of PDA, Acceptance by Final state, Acceptance by empty stack, Deterministic PDA, Equivalence of PDA and CFG, CFG to PDA and PDA to CFG, Two stack PDA. Unit - 5 Number of

lectures = 8 Title of the unit: Turing machines (TM)

Basic model, definition and representation, Instantaneous Description, Language acceptance by TM, Variants of Turing Machine, TM as Computer of Integer functions, Universal TM, Church’s Thesis, Recursive and recursively enumerable languages, Halting problem, Introduction to Undecidability, Undecidable problems about TMs. Post correspondence problem (PCP), Modified PCP, Introduction to recursive function theory. 12. Brief Description of self learning / E-learning component

13. Books Recommended (3 Text Books + 2-3 Reference Books) i. Theory of Computer Science : Automata, Languages and Computation - K.L.P. Mishra and

N.Chandrasekaran,”, PHI

ii. Introduction to Languages and Theory of Computations - Martin J. C., TMH

iii. Introduction to Automata Theory, Languages and Computation - Hopcroft, Ullman, Pearson Education

iv. Elements of the Theory of Computation - Papadimitrou, C. and Lewis, C.L, PHI

SEMESTER IV

Numerical Methods and Random process

1. Name of the Department: CSE 2. Course Name Numerical Methods

and Random process L-3 T-0 P-0

3. Course Code 13020406 4. Type of Course (use tick mark) Core () PE(√) OE() 5. Pre-requisite (if



Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus:

Unit-I: Non- Linear Equations and system of Linear Equations

Introduction, error and error propagation, Bisection method, False position Method, Method of Iteration, Newton-Raphson Method, Secant Method, Gauss Elimination method Gauss – Jordan method, Gauss – Seidel method, convergence of iterative methods. Unit-II: Interpolation: Newton‟s Forward and Backward Interpolation, Lagrange‟s Interpolation, Newton‟s Divided Difference Interpolation, Inverse Interpolation. Unit-III : Numerical Differentiation and Integration Derivations from difference tables, Higher order derivations. Newton – Cotes integra-tion formula, Trapezoidal rule, Simpson‟s rule, Boole‟s rule and Weddle‟s rule, Romberg‟s Integration . Unit-IV:Numerical Solution of Ordinary Taylor series method, Euler and modified Euler method, Runge Kutta methods, Milne‟s method, Finite Difference method. Unit-V: Partial Differential Equations Finite difference approximations of partial derivatives, Solution of Laplace‟s equation (Elliptic) by Liebmann‟s iteration method, Solution of one dimensional heat equation (Parabolic) by Bender-Schmidt method and Crank – Nicolson method, Von-Neumann stability condition, Solution of one dimensional wave equation (Hyperbolic), CFL stability condition.


To enhance problem solving skills of engineering students using a powerful problem solving tool namely numerical methods. The tool is capable of handling large systems of equations, nonlinearities and complicated geometries that are common in engineering practice but often impossible to solve analytically.


1) Apply various numerical methods and appreciate a trade off in using them. 2) Understand the source of various types of errors and their effect in using these methods. 3) To distinguish between Numerical and Analytical methods along with their Merits and demerits.

4) Understand the use of digital computers in implementation of these methods.


= 10 Non- Linear Equations and system of Linear Equations

Introduction, error and error propagation, Bisection method, False position Method, Method of Iteration, Newton-Raphson Method, Secant Method, Gauss Elimination method Gauss – Jordan method, Gauss – Seidel method, convergence of iterative methods.

Unit - 2 Number of lectures Interpolation

= 8 Newton‟s Forward and Backward Interpolation, Lagrange‟s Interpolation, Newton‟s Divided Difference Interpolation, Inverse Interpolation.

Unit - 3 Number of lectures

= 8 Numerical Differentiation and Integration

Derivations from difference tables, Higher order derivations. Newton – Cotes integra-tion formula, Trapezoidal rule, Simpson‟s rule, Boole‟s rule and Weddle‟s rule, Romberg‟s Integration .


= 8 Numerical Solution of Ordinary

Taylor series method, Euler and modified Euler method, Runge Kutta methods, Milne‟s method, Finite Difference method. Unit - 5 Number of lectures

= 8 Partial Differential Equations

Finite difference approximations of partial derivatives, Solution of Laplace‟s equation (Elliptic) by Liebmann‟s iteration method, Solution of one dimensional heat equation (Parabolic) by Bender-Schmidt method and Crank – Nicolson method, Von-Neumann stability condition, Solution of one dimensional wave equation (Hyperbolic), CFL stability condition.



13. Books Recommended (1 Text Book + 2 Reference Books)

1. Introductory Methods of Numerical Analysis: S.S. Sastry, PHI learning Pvt Ltd.

1. Numerical Methods for Scientific and Engineering computation: M.K Jain, S.R.K Iyengar and R.K Jain, New age Inter-national Publishers.

2. Numerical Method: E. Balagurusamy, Tata McGraw Hill Publication.

B.Tech-Computer Science & Engineering SEMESTER V

Personality and Career Building

1. Name of the Department: Centre for Languages & Communication 2. Course Name Personality &

Career Building L 2

T 0

P 0


any) Aptitude Building 6. Frequency (use tick

marks) Even

Odd (√) Either Sem ()

Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 28 Tutorials = 0 Practical =0 8. Brief Syllabus

i. Strategies and Skills Required for Career building/Recruitment/ Team building ii. Group Discussion and Role Play iii. Business/job Correspondence iv. Time and Work, Data Interpretation v. Algebra and Simple Reasoning


1. Negotiation skills 2. Team work 3. Ready to apply for a job 4. Implementing logical Aptitude in decision making

10. Course Outcomes (COs): i. able to get an idea of industry perspective ii. able to Able to develop a logical thought process related to every aspect of life iii. to interpret data and convert it into information iv. able to hold meaningful group discussions v. able to develop and respond to daily situations using critical thinking


= 3, practical=3 Title of the unit: Strategies and Skills Required for Career building/Recruitment/ Team building

Learning of different strategies to be used: Negotiation, Assertions, Politeness through Conversation, Assertive Strategies, Leadership Skills, Team Work, Management Skills through Group Activities

Unit - 2 Number of lectures = 2, practical= 2

Title of the unit: Group Discussion and Role Play

Listening and Speaking Comprehension through Group Discussion and audio-visual aids, Do’s and Don’ts of Group Discussions related to various topics (Day- Today life/Social Issues/Political and others Unit - 3 Number of lectures

= 3, practical=3 Title of the unit: Business/job Correspondence

Resume Writing, Letter Writing, Job Application Letter Unit - 4 Number of lectures

= 3, practical=3 Title of the unit: Time and Work, data Interpretation

Time and Work, Time speed distance, Table, Line Graph, bar Graph, Cube, Dice, Calendars, Test on Pie and Bar Charts, Comprehensive Practice Test-I on Area Covered, Comprehensive Practice test-2 on Area Covered


=3, practical=3 Title of the unit: Algebra and Simple Reasoning

Linear and Quadratic Equation, Function Basics, Inequalities, Progression, Set Theory/ Venn Diagram, Pie Chart, Permutation and Combination, Probability, Visual reasoning, Alphabet based reasoning 12. Brief Description of self learning / E-learning component

The students will be encouraged to learn using the SGT ELearning portal and choose the relevant lectures

delivered by subject experts of SGT University. The link to the E-Learning portal: https://elearning.sgtuniversity.ac.in/course-category/general/

13. Books Recommended (3 Text Books + 2-3 Reference Books) 1. Sanjay Kumar and Pushp Lata ‘Communication Skills’, OUP 2012 2. Raymond Murphy ‘Essential English Grammar’, Cambridge University Press 1998 3. Meenakshi Raman and Sangeeta Sharma ‘Technical Communication Principle and Practice’, OUP 2012 4. Meenakshi Raman and Prakash ‘Business Communication’ OUP 2011 5. Hory Samkar Mukerjee ‘Business Communication Connecting at Work’ OUP 2013


Sr. No. Title CO covered (taken from S.No. 10)

1 Strategies and Skills Required for Career building/Recruitment/ Team building

(i),(ii), (iv)

2 Group Discussion and Role Play (i), (iv) 3 Business/job Correspondence (i) 4 Time and Work, Data Interpretation (iv) 5 Algebra and Simple Reasoning (iv), (v)


Sr. No. Title CO covered 1 Negotiation techniques-I (v) 2 Understanding Personal Negotiation Styles (v) 3 Role Play- Negotiation Techniques (v) 4 Team Building Activity-I (iv) 5 Team Building Activity-II (iv) 6 Assertive Behaviour Quiz (i) 7 Group Discussion- Current Affairs (iv) 8 Role Play- Daily Situations (v) 9 Resume writing (i), (ii) 10 Cover Letter/ Job Application Letter and Email writing (i), (ii)


SEMESTER V

Compiler Design

1. Name of the Department: CSE 2. Course Name Compiler design L T P 3. Course Code 3 0 0 4. Type of Course (use tick mark) Core (√ ) PE() OE() 5. Pre-requisite (if

any) TOC 6. Frequency (use tick


Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus COURSE CONTENT Unit I: Introduction Introduction to Compiler, Phases and passes, Bootstrapping, Finite state machines and regularexpressions and their applications to lexical analysis, Optimization of DFA-Based PatternMatchers implementation of lexical analyzers, lexical-analyzer generator, LEX-compiler,Formal grammars and their application to syntax analysis, BNF notation, ambiguity, YACC.The syntactic specification of programming languages: Context free grammars, derivation andparse trees, capabilities of CFG. Unit II: Basic Parsing Techniques Parsers, Shift reduce parsing, operator precedence parsing, top down parsing, predictive parsers Automatic Construction of efficient Parsers: LR parsers, the canonical Collection of LR (0) items, constructing SLR parsing tables, constructing Canonical LR parsing tables, Constructing LALR parsing tables, using ambiguous grammars, an automatic parser generator, and implementation of LR parsing tables. Unit III: Syntax-directed Translation Syntax-directed Translation schemes, Implementation of Syntax directed Translators, Intermediate code, postfix notation, Parse trees & syntax trees, three address code, quadruple & triples, translation of assignment statements, Boolean expressions, statements that alter the flow of control, postfix translation, translation with a top down parser. More about translation: Array references in arithmetic expressions, procedures call, declaration sand case statements. Unit IV: Symbol Tables Data structure for symbols tables, representing scope information. Run-Time Administration: Implementation of simple stack al-location scheme, storage allocation in block structured language. Error Detection & Recovery: Lexical Phase errors, syntactic phase errors semantic errors. Unit V: Code Generation Selected Topics: Algebraic Computation, Fast Fourier Transform, String Matching, Theory of NP-completeness, Approximation algorithms and Randomized algorithms. . 9. Learning objectives:

1. Provide an understanding of the fundamental principles in compiler design 2. Provide the skills needed for building compilers for various situations that one may encounter in a

career in Computer Science. 3. Learn the process of translating a modern high-level language to executable code required for compiler

construction. 10. Course Outcomes:


1. Understand fundamentals of compiler and identify the relationships among different phases of the compiler. 2. Understand the application of finite state machines, recursive descent, production rules, parsing, and language

semantics. 3. Analyze & implement required module, which may include front-end, back-end, and a small set of middle-end

optimizations. 4. Use modern tools and technologies for designing new compiler.

11. Unit wise detailed content

Unit-1 Number of lectures = 10

Title of the unit: Introduction

Introduction to Compiler, Phases and passes, Bootstrapping, Finite state machines and regular expressions and their applications to lexical analysis, Optimization of DFA-Based Pattern Matchers implementation of lexical analyzers, lexical-analyzer generator, LEX-compiler, Formal grammars and their application to syntax analysis, BNF notation, ambiguity, YACC. The syntactic specification of programming languages: Context free grammars, derivation and parse trees, capabilities of CFG. Unit - 2 Number of lectures

=8 Title of the unit: Basic Parsing Techniques

Parsers, Shift reduce parsing, operator precedence parsing, top down parsing, predictive parsers Automatic Construction of efficient Parsers: LR parsers, the canonical Collection of LR (0) items, constructing SLR parsing tables, constructing Canonical LR parsing tables, Constructing LALR parsing tables, using ambiguous grammars, an automatic parser generator, and implementation of LR parsing tables. Unit - 3 Number of lectures

= 8 Title of the unit: Syntax-directed Translation

Syntax-directed Translation schemes, Implementation of Syntax directed Translators, Intermediate code, postfix notation, Parse trees & syntax trees, three address code, quadruple & triples, translation of assignment statements, Boolean expressions, statements that alter the flow of control, postfix translation, translation with a top down parser. More about translation: Array references in arithmetic expressions, procedures call, declaration sand case statements. Unit - 4 Number of lectures

= 8 Title of the unit: Symbol Tables

Data structure for symbols tables, representing scope information. Run-Time Administration: Implementation of simple stack al-location scheme, storage allocation in block structured language. Error Detection & Recovery: Lexical Phase errors, syntactic phase errors semantic errors. Unit - 5 Number of lectures

= 8 Title of the unit: Code Generation

Selected Topics: Algebraic Computation, Fast Fourier Transform, String Matching, Theory of NP-completeness, Approximation algorithms and Randomized algorithms. 12. Brief Description of self learning / E-learning component Online Video Lectures on Analysis and design of algorithms Practice of Algorithims 13. Books Recommended (2 Text Books + 2 Reference Books)

1. ALFRED V AUTOR AHO, JEFFREY D AUTOR ULLMAN “Principles of Compiler Design”. 2. V Raghvan, “ Principles of Compiler Design”, TMH

REFERENCE BOOKS 1. Aho, Sethi & Ullman, “Compilers: Principles, Techniques and Tools”, Pearson Education2 2. Charles Fischer and Ricard LeBlanc,” Crafting a Compiler with C”, Pearson Education

SEMESTER V

Software Engineering

1. Name of the Department: CSE 2. Course Name Software

Engineering L T P

3. Course Code 13020507 3 0 2 4. Type of Course (use tick mark) Core (√ ) PE() OE() 5. Pre-requisite (if



Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28 8. Brief Syllabus COURSE CONTENT Unit I: Introduction to Software Engineering Software Components, Software Characteristics, Software Crisis, Software Engineering Processes, Similarity and Differences from Conventional Engineering Processes, Software Quality Attributes. Software Development Life Cycle (SDLC) Models: Water Fall Model, Prototype Model, Spiral Model, Evolutionary Development Models, Iterative Enhancement Models. Unit II: Software Requirement Specifications (SRS) Requirement Engineering Process: Elicitation, Analysis, Documentation, Review and Management of User Needs, Feasibility Study, Information Modeling, Data Flow Diagrams, Entity Relationship Diagrams, Decision Tables, SRS Document, IEEE Stan-dards for SRS. Software Quality Assurance (SQA): Verification and Validation, SQA Plans, Software Quality Frameworks, ISO 9000 Models, SEI-CMM Model. Unit III: Software Design Basic Concept of Software Design, Architectural Design, Low Level Design: Modularization, Design Structure Charts, Pseudo Codes, Flow Charts, Coupling and Cohesion Measures, Design Strategies: Function Oriented Design, Object Oriented Design, Top-Down and Bottom-Up Design. Software Measurement and Metrics: Various Size Oriented Measures: Halestead’s Software Science, Function Point (FP) Based Measures, Cyclomatic Complexity Measures: Control Flow Graphs. Unit IV: Software Testing Testing Objectives, Module Testing, Integration Testing, Acceptance Testing, Regression Testing, Testing for Functionality and Testing for Performance, Top-Down and Bottom-Up Testing Strategies: Test Drivers and Test Stubs, Structural Testing (White Box Testing), Functional Testing (Black Box Testing), Test Data Suit Preparation, Alpha and Beta Testing of Products. Static Test-ing Strategies: Formal Technical Reviews (Peer Reviews), Walk Through, Code Inspection, Compliance with Design and Coding Standards. Unit V: Software Maintenance and Software Project Management Software as an Evolutionary Entity, Need for Maintenance, Categories of maintenance: Preventive, Corrective and Perfective Main-tenance, Cost of Maintenance, Software Re-Engineering, Reverse Engineering. Software Configuration Management Activities, Change Control Process, Software Version Control, an Overview of CASE Tools. Estimation of Various Parameters such as Cost, Efforts, Schedule/Duration, Constructive Cost Models (COCOMO), Resource Allocation Models, Software Risk 9. Learning objectives:

5. Discuss the evolution of software engineering concepts. 6. Understand the structure of Software engineering and development techniques. 7. To elicit, analyze and specify software requirements through a productive working relationship with project

stakeholders. 8. Analyze and implement application of network system


At the end of the course student will be able to: 1. To apply software engineering theory, principles, tools and processes, as well as the theory and principles of

computer science and mathematics, to the development and maintenance of complex software systems. 2. To design and validate various software prototypes and to develop quality software metrics. 3. To participate, productively in software project teams involving students from both software engineering and

other majors streams of computer science & engineering.

4. To design and develop standard procedures through oral and written reports and software documentation evaluated by both peers and faculty.


= 10 Title of the unit: Introduction to SE

Software Components, Software Characteristics, Software Crisis, Software Engineering Processes, Similarity and Differences from Conventional Engineering Processes, Software Quality Attributes. Software Development Life Cycle (SDLC) Models: Unit - 2 Number of lectures

= 8 Title of the unit: Software Requirement Specifications (SRS)

Requirement Engineering Process: Elicitation, Analysis, Documentation, Review and Management of User Needs, Feasibility Study, Information Modeling, Data Flow Diagrams, Entity Relationship Diagrams, Decision Tables, SRS Document, IEEE Standards for SRS,Software Quality Assurance (SQA):. Unit - 3 Number of lectures

= 8 Title of the unit: Software Design

Basic Concept of Software Design, Architectural Design, Low Level Design: Modularization, Design Structure Charts, Pseudo Codes, Flow Charts, Coupling and Cohesion Measures, Design Strategies: Function Oriented Design, Object Oriented Design, Top-Down and Bottom-Up Design. Software Measurement and Metrics. Unit - 4 Number of lectures

= 8 Title of the unit: Software Testing

Testing Objectives, Module Testing, Integration Testing, Acceptance Testing, Regression Testing, Testing for Functionality and Testing for Performance, Top-Down and Bottom-Up Testing Strategies: Test Drivers and Test Stubs, Structural Testing (White Box Testing), Functional Testing (Black Box Testing), Unit - 5 Number of lectures

= 8 Title of the unit: Software Maintenance and Software Project Management

Software as an Evolutionary Entity, Need for Maintenance, Categories of maintenance: Preventive, Corrective and Perfective Maintenance, Cost of Maintenance, Software Re-Engineering, Reverse Engineering. COCOMO. 12. Brief Description of self learning / E-learning component Online Video Lectures on computer networks Practice of networking, Algorithims 13. Books Recommended (1Text Books + 4 Reference Books)

1. R. S. Pressman, Software Engineering: A Practitioners Approach, McGraw Hill. 2. K. K. Aggarwal and Yogesh Singh, Software Engineering, New Age International Publishers.

REFERENCE BOOKS 1. Rajib Mall, Fundamentals of Software Engineering, PHI Publication. 2. Pankaj Jalote, Software Engineering, Wiley


Sr. No. Title CO covered 1 Introduction to SE (i) 2 Software Requirement Specifications (SRS) (ii) 3 Software Design (iii) 4 Software Testing (iv) 5 Software maintenance and spm (iv)


Sr. No. Title CO covered 1 Introduction to software engineering class diagram, use case diagram (i) 2 Implement requirement gathering diagrams (ii) 3 Write a program for system design (iii) 4 To Create, compile, link and test your assigned objects or modules diagrams (iv) 6 Complete project schedule using Gantt Chart (iv) 7 Perform dynamic testing (Beta Testing). (ii) 8 Perform white box testing on individual software components while aggregates (iii) 9 Make realistic approach of unit testing and integration strategy (i)

SEMESTER V

Analysis and Design of Algorithm

1. Name of the Department: CSE 2. Course Name ADA L T P 3. Course Code 13020505 3 0 0 4. Type of Course (use tick mark) Core (√ ) PE() OE() 5. Pre-requisite (if

any) Fundamental of C 6. Frequency (use tick


Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus COURSE CONTENT Unit I: Introduction Introduction: Algorithms, Analyzing algorithms, Complexity of algorithms, Growth of functions, Performance measurements, Sorting and order Statistics - Shell sort, Quick sort, Merge sort, Heap sort, Comparison of sorting algorithms, Sorting in linear time. Unit II: Advanced Data Structures Advanced Data Structures: Red-Black trees, B – trees, Binomial Heaps, Fibonacci Heaps. Unit III : Divide & Conquer and Greedy Methods Divide and Conquer with examples such as Sorting, Matrix Multiplication, Convex hull and Searching. Greedy methods with examples Huffman Coding, Knapsack, Minimum Spanning trees – Prim’s and Kruskal’s algorithms, Single source shortest paths - Dijkstra’s and Bellman Ford algorithms. Unit IV: Dynamic Programming Dynamic programming with examples such as Knapsack, All pair shortest paths –Warshal’s and Floyd’s algorithms, Resource allocation problem. Backtracking, Branch and Bound with examples such as Travelling Salesman Problem, Graph Coloring, n-Queen Problem, Hamiltonian Cycles and Sum of subsets. Unit V Algebraic computation, String Matching, Theory of NP-completeness, Approximation algorithms and Randomized algorithms. 9. Learning objectives:

1. Existing algorithm and develop efficient algorithms for simple computational tasks. 2. Reasoning about the correctness of the algorithm 3. Behaviors’ of algorithms and the notion of tractable and intractable problems.


At the end of the course student will be able to: 1. Analyze algorithms and determine efficiency of algorithm. 2. Understand advanced abstract data type (ADT), data structures and their implementations 3. Design algorithms using the brute force, greedy, divide and conquer, branch and bound etc. methodologies. 4. Prove problems of P, NP, or NP-Complete. 5. Develop and implement learned/new algorithm using appropriate techniques to solve problems.



Algorithms, Analyzing algorithms, Complexity of algorithms, Growth of functions, Performance measurements, Sorting and order Statistics - Shell sort, Quick sort, Merge sort, Heap sort, Comparison of sorting algorithms, Sorting in linear time. Unit - 2 Number of lectures

=8 Title of the unit: Advanced Data Structures

Advanced Data Structures: Red-Black trees, B – trees, Binomial Heaps, Fibonacci Heaps. Unit - 3 Number of lectures

= 8 Title of the unit: Divide & Conquer and Greedy Methods

Divide and Conquer with examples such as Sorting, Matrix Multiplication, Convex hull and Searching. Greedy methods with examples Huffman Coding, Knapsack, Minimum Spanning trees – Prim’s and Kruskal’s algorithms, Single source shortest paths - Dijkstra’s and Bellman Ford algorithms. Unit - 4 Number of lectures

= 8 Title of the unit: Dynamic Programming

Dynamic programming with examples such as Knapsack, All pair shortest paths –Warshal’s and Floyd’s algorithms, Resource allocation problem. Backtracking, Branch and Bound with examples such as Travelling Salesman Problem, Graph Coloring, n-Queen Problem, Hamiltonian Cycles and Sum of subsets. Unit - 5 Number of lectures

= 8 Title of the unit: Computation

Algebraic computation, String Matching, Theory of NP-completeness, Approximation algorithms and Randomized algorithms. 12. Brief Description of self learning / E-learning component Online Video Lectures on Analysis and design of algorithms Practice of Algorithims 13. Books Recommended (1Text Books + 4 Reference Books)

1. Thomas H. Coreman, Charles E. Leiserson and Ronald L. Rivest, “Introduction to Algorithms”, Printice Hall of India.

2. RCT Lee, SS Tseng, RC Chang and YT Tsai, “Introduction to the Design and Analysis of Algorithms”, Mc Graw Hill, 2005

REFERENCE BOOKS 1. E. Horowitz & S Sahni, “Fundamentals of Computer Algorithms”, 2. Berman, Paul,” Algorithms”, Cengage Learning. 3. Aho, Hopcraft, Ullman, “The Design and Analysis of Computer Algorithms” Pearson Education, 2008.

Tutorial / Extended Tutorial /presentation/Case study components

Sr. No. Title CO covered 1 Introduction 2 Advanced Data Structures 3 Divide & Conquer and Greedy Methods 4 Dynamic Programming 5 Computation

SEMESTER V

Python Programming

1. Name of the Department: CSE 2. Course Name Python

Programming L-3 T-0 P-2


any) Programming

Language 6. Frequency (use tick


Sem () Every Sem ()


Brief Syllabus: An introduction to the Python programming language. Covers details of how to start and stop the interpreter and write programs. Introduces Python's basic datatypes, files, functions, and error handling.

8. Learning objectives: To Learn concepts of various Python script at the shell prompt, Python types, expressions to solve relative problems. 9. Course Outcomes:

5) To utilize high-level data types such as lists and dictionaries 6) To import and utilize a module • read from and write to a text file. 7) understand the difference between mutable and immutable types

8) To demonstration of IDE‟s: IDLE, IPython, IPython Notebook, hosted environments.


= 12 Title of the unit: Introduction to Python.

Introduces Python's basic datatypes, files, functions, and error handling. Working with Data. A detailed tour of how to represent and work with data in Python. Covers tuples, lists, dictionaries, and sets. Students will also learn how to effectively use Python's very powerful list processing primitives such as list comprehensions. Finally, this section covers critical aspects of Python's underlying object model including variables, reference counting, copying, and type checking. Unit - 2 Number of lectures

= 10 Title of the unit: Program Organization and Functions

More information about how to organize larger programs into functions. A major focus of this section is on how to design functions that are reliable and can be easily reused in other settings. Also covers technical details of functions including scoping rules and documentation strings. Modules and Libraries. How to organize programs into modules and details on using modules as a tool for creating extensible programs. Concludes with a tour of some of the most commonly used library modules including those related to system administration, text processing, subprocesses, XML parsing, binary data handling, and databases. Also includes information on how to install third-party library modules Unit - 3 Number of lectures

= 10 Title of the unit: Classes and Objects

An introduction to object-oriented programming in Python. Describes how to create new objects, overload operators, and utilize Python special methods. Also covers basic principles of object oriented programming including inheritance and composition. Inside the Python Object System. A detailed look at how objects are implemented in Python. Major topics include object representation, attribute binding, inheritance, memory management, and special properties of classes including properties, slots, and private attributes. Unit - 4 Number of lectures

= 10 Title of the unit: , Debugging, and Software Development Practice

This includes effective use of documentation strings, program testing using both the doctest and unittest modules, and

effective use of assertions. The Python debugger and profiler are also described. Iterators and Generators. Covers the iteration protocol, iterable objects, generators and generator expressions. A major focus of this section concerns the use of generators to set up data processing pipelines--a particularly effective technique for addressing a wide variety of common systems programming problems (e.g., processing large datafiles, handling infinite data streams, etc.). Text I/O Handling. More information on text-based I/O. Topics include text generation, template strings, and Unicode. Some Advanced Topics. A variety of more advanced programming topics including variable argument functions, anonymous functions (lambda), closures, decorators, static and class methods, and packages. Python Integration Primer. A survey of how Python is able to interact with programs written in other programming languages. Topics include network programming, accessing C code, COM extensions, Python, and Iron Python. 11. Brief Description of self learning / E-learning component. This learning method gives students to find out their learning capability. Students involve some sort of choice in this

learning. As self directed learning learners can determine which modules or scenarios to review again and again.

12. Books Recommended (2 Text Book + 4 Reference Books) 1. Learning to Program Using Python by Cody Jackson 2. Python for complete beginners by Dr. Martin Jones

3. Fundamentals of Python: First Programs by Ken Lambert 4. Learning Python, 5th Edition by Mark Lutz, O'Reilly Media. 5. Easy GUI Programming in Python by Ken Lambert 6. The Practice of Computing Using Python by Bill Punch and Rich Enbody

Lab Component Components

Sr. No. Title CO covered 1 Demonstrate the working of ‘id’ and ‘type’ functions 2 To find all prime numbers within a given range. 3 To print ‘n terms of Fibonacci series using iteration. 4 To demonstrate use of slicing in string 5 To add 'ing' at the end of a given string (length should be at least 3). 6 To compute the frequency of the words from the input. The output should output after

sorting the key alphanumerically

7 Write a program that accepts a sequence of whitespace separated words as input and prints the words after removing all duplicate words and sorting them alphanumerically.

8 To demonstrate use of list & related functions 9 To demonstrate use of Dictionary& related functions 10 To demonstrate use of tuple, set& related functions 11 To implement stack using list 12 To implement queue using list 13 To read and write from a file 14 To copy a file 15 To demonstrate working of classes and objects 16 To demonstrate class method & static method 17 To demonstrate constructors 18 To demonstrate inheritance 19 To demonstrate aggregation/composition 20 To create a small GUI application for insert, update and delete in a table using Oracle as

backend and front end for creating form

SEMESTER V

Distributed Database Management System

1. Name of the Department: CSE 2. Course Name Distributed Database

Management System L 3

T 0

P 2

3. Course Code 13020536

https://www.createspace.com/3611970

http://www.amazon.com/Python-complete-beginners-friendly-experience/dp/1514376989/

http://www.cengagebrain.com/shop/isbn/9781111822705

http://home.wlu.edu/%7Elambertk/breezypythongui/easyguibook.html

http://www.pearsonhighered.com/educator/product/Practice-of-Computing-using-Python-The/9780136110675.page

4. Type of Course (use tick mark) Core () PE(√) OE() 5. Pre-requisite (if

any) DBMS 6. Frequency (use tick

marks) Even ()

Odd (√) Either Sem ()

Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28 8. Brief Syllabus Unit I: Introduction to Distributed Database Distributed Data Processing, Distributed Database Systems, Promises of DDBSs, Complicating factors, Problem areas , Overview of RDBMS: Concepts, Integrity, NormalizationDistributed DBMS Architecture : Models– Autonomy, Distribution, Heterogeneity DBMS Architecture – Client/Server, Peer to peer, MDBS. Unit II: Database Design Data Distribution Alternatives: Design Alternatives – localized data, distributed data, Fragmentation – Vertical, Horizontal (primary & derived), hybrid, general guidelines, correctness rules, Distribution transparency – location, fragmentation, replication , Impact of distribution on user queries – No Global Data. Unit III: Semantic Data Control View Management,Authentication – database authentication, OS authentication, Access Rights, Semantic Integrity Control – Centralized & Distributed ,Cost of enforcing semantic integritySuperscalar operation. UNIT IV: Query Processing : Query Processing Problem, Layers of Query Processing, Query Processing in Centralized Systems – Parsing & Translation, Optimization, Code generation, Query Processing in Distributed Systems – Mapping global query to local, Optimization, Optimization of Distributed Queries: Query Optimization,Centralized Query Optimization,Join Ordering, Distributed Query Optimization Algorithms Unit V: Distributed Transaction Management & Concurrency Control: Transaction concept, ACID property,Objectives of transaction management, Types of transactions,Objectives of Distributed Concurrency Control, Concurrency Control anomalies,Methods of concurrency control, Serializability and recoverability, Distributed Serializability, Enhanced lock based and timestamp based protocols. 9. Learning objectives: The objective of this course is to:

• explain the organization of the classical Dbms and its major functional Modules. • explain how a Distributed database works . • provide knowledge of database design and data control in detail. • illustrate how transactions and query processing is performed.



• understand and analyze distributed database • understand I/O system and interconnection structures of DDBMS • understand and analyze different query processing and data control.


= 10, practical=3 Title of the unit: Presentation Strategies

Distributed Data Processing, Distributed Database Systems, Promises of DDBSs, Complicating factors, Problem areas , Overview of RDBMS: Concepts, Integrity, NormalizationDistributed DBMS Architecture : Models– Autonomy, Distribution, Heterogeneity DBMS Architecture – Client/Server, Peer to peer, MDBS Unit - 2 Number of lectures

=8, practical=2 Title of the unit: Situation Based Conversation

Database Design Data Distribution Alternatives: Design Alternatives – localized data, distributed data, Fragmentation – Vertical, Horizontal (primary & derived), hybrid, general guidelines, correctness rules, Distribution transparency – location, fragmentation, replication , Impact of distribution on user queries – No Global Data. Unit - 3 Number of lectures

= 8, practical=3 Title of the unit: Professional Skills

View Management,Authentication – database authentication, OS authentication, Access Rights, Semantic Integrity Control – Centralized & Distributed ,Cost of enforcing semantic integritySuperscalar operation Unit - 4 Number of lectures

= 8, practical=3 Title of the unit: Group Discussions and Role Play

Query Processing Problem, Layers of Query Processing, Query Processing in Centralized Systems – Parsing & Translation, Optimization, Code generation, Query Processing in Distributed Systems – Mapping global query to local, Optimization, Optimization of Distributed Queries: Query Optimization,Centralized Query Optimization,Join Ordering, Distributed Query Optimization Algorithms Unit - 5 Number of lectures

=8, practical=3 Title of the unit: Mock Interviews

Transaction concept, ACID property,Objectives of transaction management, Types of transactions,Objectives of Distributed Concurrency Control, Concurrency Control anomalies,Methods of concurrency control, Serializability and recoverability, Distributed Serializability, Enhanced lock based and timestamp based protocols. 12. Brief Description of self learning / E-learning component



13. Books Recommended (3 Text Books + 2-3 Reference Books)

• Stefano Ceri, Giuseppe Pelagatti, Distributed Databases Principles & Systems, McGraw-Hill.

• M.Tamer Ozsu, Patrick Valduriez, Distributed database systems, 2nd Edition, Prentice Hall of India, New Delhi.

i. Lab component components

Sr. No. Title CO covered 1 Create two databases either on single DBMS and Design Database to

fragment and share the fragments from both database and write single query for creating view.

2 Create two databases on two different computer systems and create database view to generate single DDB.

3 Create various views using any one of examples of database and Design various constraints.

4 Write and Implement algorithm for query processing using any of Example in either C /C++ /Java / .NET

5 Using any of example, write various Transaction statement and show the information about concurrency control [i.e. various lock’s from dictionary] by executing multiple update and queries.

6 Using Transaction /commit rollback, Show the transaction ACID properties. 7 Write java JDBC program and use JTA to show various isolation level’s in

transaction.

8 Implement Two Phase Commit Protocol 9 Case study on noSQL 10 Case study on Hadoop


B.Tech-Computer Science & Engineering SEMESTER VI

Campus to Corporate

1. Name of the Department: Centre for Languages & Communication 2. Course Name Campus to

Corporate L 1

T 0

P 2


any) Personality Development and Career Building


Even (√)


Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 14 Tutorials = 0 Practical = 2*14=28 8. Brief Syllabus Presentation strategies Situation based Conversation Professional Skills Group Discussion and Role Play Mock Interviews 9. Learning objectives:

i. To prepare students for smooth transition from campus to corporate ii. To equip students with interview acing skills iii. To build up formal conversational skills iv. To facilitate meaningful discussions for amicable problem solving


iv) able to make formal presentations using basic business communication v) able to hold formal business conversations confidently vi) able to conduct business meetings with right etiquettes vii) able to hold meaningful group discussions and ace interviews


= 3, practical=3 Title of the unit: Presentation Strategies

Defining purpose, audience and locale, organizing content, Preparing outlines ,audio-visual aids, nuances of body language ,space, setting nuances and voice dynamics, build confidence, handling questions, collocations to be used for day to day conversation, improve the ability to present in front of the group Unit - 2 Number of lectures

=3, practical=2 Title of the unit: Situation Based Conversation

Conversations in Pairs to be Conducted (based on situations related to day-today life), Enhancing communication Skills through Situation Based Conversations. Unit - 3 Number of lectures

= 3, practical=3 Title of the unit: Professional Skills

Meetings, Agenda, Minutes of the Meeting, Business Etiquette. Unit - 4 Number of lectures

= 2, practical=3 Title of the unit: Group Discussions and Role Play

Personality Traits to be evaluated, Dynamics of Group Behavior, Group Etiquettes and Mannerism, Tips for Effective Group Discussion, Situation Based Role Play in Groups

Unit - 5 Number of lectures =3, practical=3

Title of the unit: Mock Interviews

Practice through Mock Interviews for Recruitment. 12. Brief Description of self learning / E-learning component



13. Books Recommended (3 Text Books + 2-3 Reference Books)

ii. E. Suresh Kumar, P. Sreehari and J. Savithri ‘Communication Skills and Soft Skills An Integrated Approach’, Pearson 2012

iii. Nitin Bhatnagar and Mamta Bhatnagar ‘Effective Communication and Soft Skills: Strategies for Success’, Pearson 2012

iv. Francis Peter S. J ‘Soft Skills and Professional Communication’, Tata McGraw-Hill 2012 v. Barun K. Mitra ‘Personality Development and Soft Skills’, Oxford University Press 2011 vi. Dr. Seema Miglani, Shikha Goyal and Rohit Phutela ‘Communication Skills-II’, Vayu Education of India

2009 vii. L. Ann Masters and Harold R. Wallace ‘Personal Development for life and Work’ Cengage Learning 2012. viii. Tutorial / Extended Tutorial /presentation/Case study components

Sr. No. Title CO covered 1 Presentation strategies (i) 2 Situation based Conversation (ii) 3 Professional Skills (i), (ii), (iii) 4 Group Discussion and Role Play (i), (iii), (iv) 5 Mock Interviews (iv)

ix. Lab component components

Sr. No. Title CO covered 1 Making PowerPoint Presentations on topics assigned in the class -I (i) 2 Making PowerPoint Presentations on topics assigned in the class -II (i) 3 Role Play- Body Language (ii), (iii) 4 Situational Conversation-I (ii), (iii) 5 Situational Conversation-II (ii), (iii) 6 Prepare meetings agenda (iii) 7 Conduct meeting on the basis of agenda framed (iii) 8 Group Discussion-I (iv) 9 Group Discussion-II (iv) 10 Mock Interviews (Minimum 2 rounds) (iv)


SEMESTER VI

Microprocessor and Interfacing

1. Name of the Department: CSE 2. Course Name Microprocessor and

Interfacing L-3 T-0 P-0

3. Course Code 13020673 4. Type of Course (use tick mark) Core (√) PE(√) OE() 5. Pre-requisite (if


marks) Even (√)


Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = Brief Syllabus:.

Unit I

THE 8085 PROCESSOR : Introduction to microprocessor, Pin layout,Architecture, instruction set, interrupt structure,Addressing modes and Assembly language programming for arithmetic functions.

Unit II

THE 8086 MICROPROCESSOR ARCHITECTURE : Architecture, block diagram of 8086, Pin layout, memory segmentation and physical address computations,Interrupt logic description of various signals.

Unit III

INSTRUCTION SET OF 8086 : Instruction execution timing, assembler instruction format, addressing modes, Instructions set ,directives , programming examples for mathematical function.

Unit IV

INTERFACING DEVICE : Additional IC Operations: 8255,8254,8259A,8237.

Interfacing of LED’s, LCD, keyboard, Seven segment motor.

8. Learning objectives: The student will be able to select an appropriate ‘architecture’ or program design to apply to a particular situation; e.g. an interrupt-driven I/O handler for a responsive real-time machine. Following on from this, the student will be able to design and build the necessary programs. 9. Course Outcomes:

d. Recall and apply a basic concept of digital fundamentals to Microprocessor based personal computer

system. e. Identify a detailed s/w & h/w structure of the Microprocessor. f. Illustrate how the different peripherals (8255, 8253 etc.) are interfaced with Microprocessor.


= 12 Title of the unit: THE 8085 PROCESSOR

THE 8085 PROCESSOR : Introduction to microprocessor, Pin layout,Architecture, instruction set, interrupt structure,Addressing modes and Assembly language programming for arithmetic functions.


= 10 Title of the unit: THE 8086 MICROPROCESSOR ARCHITECTURE

THE 8086 MICROPROCESSOR ARCHITECTURE : Architecture, block diagram of 8086, Pin layout, memory segmentation and physical address computations,Interrupt logic description of various signals.

Unit – 3 Number of lectures = 10

Title of the unit: INSTRUCTION SET OF 8086

INSTRUCTION SET OF 8086 : Instruction execution timing, assembler instruction format, addressing modes, Instructions set ,directives , programming examples for mathematical function.


Title of the unit: INTERFACING DEVICE

INTERFACING DEVICE: Additional IC Operations: 8255, 8254, 8259A, 8237.

Interfacing of LED’s, LCD, keyboard, Seven segment motor.



12. Books Recommended (1 Text Books + 3-4 Reference Books) 1) 1. Microprocessor Architecture, Programming & Applications with 8085 : Ramesh S Gaonkar; Wiley Eastern

Ltd.

2) 2. The Intel Microprocessors 8086- Pentium processor : Brey; PHI

3) 3. Microprocessors and interfacing : Hall; TMH

4) 4. The 8088 & 8086 Microprocessors-Programming, interfacing,Hardware & Applications :Triebel & Singh; PHI

1) 3. Microcomputer systems: the 8086/8088 Family: architecture, Programming & Design : Yu-Chang Liu & Glenn A Gibson; PHI

2) 4. Advanced Microprocessors and Interfacing : Badri Ram; TMH


Sr. No. Title CO covered 1 Study of 8085 Microprocessor kit.

2 a. Addition of two 8-bit numbers.

b. Addition of two 8-bit numbers (with carry).

Write a program using 8085 and verify for :

3 Write a program using 8085 and verify for :

a. 8-bit subtraction (display borrow)

b. 16-bit subtraction (display borrow)

4 Write a program using 8085 for multiplication of two 8- bit numbers by repeated

addition method. Check for minimum number of additions and test for typical data.

5 Write a program using 8085 for multiplication of two 8- bit numbers by bit rotation

method and verify.

6 Write a program using 8085 for division of two 8- bit numbers by repeated subtraction method and test for typical data.

7 Write a program using 8085 for dividing two 8- bit numbers by bit rotation method and test for typical data.

8 Study of 8086 microprocessor kit

9 Write a program using 8086 for division of a defined double word (stored in a data segment) by another double Word division and verify.

10 Write a program using 8086 for finding the square root of a given number and verify.

11 Write a program using 8086 for copying 12 bytes of data from source to destination and verify.

12 Write a program using 8086 for copying 12 bytes of data from source to destination and verify.

13 Write a program using 8086 for arranging an array of numbers in descending order and verify.

14 Write a program using 8086 for arranging an array of numbers in ascending order and verify.

15 Write a program for finding square of a number using look-up table and verify.

16 Write a program to interface a two digit number using seven-segment LEDs. Use 8085/8086 microprocessor and 8255 PPI.

17 Write a program to control the operation of stepper motor using 8085/8086 microprocessor and 8255 PPI.

Note: At least ten experiments have to be performed.

SEMESTER VI

Web Security

1. Name of the Department: CSE 2. Course Name Web Security L T P 3. Course Code 13020669 3 0 0 4. Type of Course (use tick mark) Core (√) PE() OE() 5. Pre-requisite (if


marks) Even (√)


Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus: UNIT I

INTRODUCTION & NUMBER THEORY Services, Mechanisms and attacks-the Encryption techniques (Symmetric cipher model, substitution techniques, transposition techniques, steganography).

Unit II

BLOCK CIPHERS & PUBLIC KEY CRYPTOGRAPHY Data Encryption Standard-Block cipher principles-block cipher modes of operation-Advanced Encryption Standard (AES)-Triple DES algorithm. Public key cryptography: Principles of public key cryptosystems-The RSA algorithm-Key management - Diffie Hellman Key exchange

UNIT III

SECURITY PRACTICE & SYSTEM SECURITY Web Security-: Application security (Database, E-mail and Internet), Data Security Considerations-Backups, Archival Storage and Disposal of Data, Security Technology-Firewall and VPNs, Intrusion Detection, Access Control.

Security Threats -Viruses, Worms, Trojan Horse, Bombs, Trapdoors, Spoofs, E-mail viruses, Macro viruses, Malicious Software, Network and Denial of Services Attack, Security Threats to E-Commerce-Electronic Payment System, e-Cash, Credit/Debit Cards, Hash Function and Digital Signature UNIT IV

E-MAIL, IP Security E-mail Security: Security Services for E-mail-attacks possible through E-mail - establishing keys privacy-authentication of the source-Message Integrity-Non-repudiation-Pretty Good Privacy-S/MIME.

IPSecurity: Overview of IPSec - IP and IPv6-Authentication Header-Encapsulation Security Payload (ESP)-Internet Key Exchange (Phases of IKE, ISAKMP/IKE Encoding).


7. Develop a foundation of set theory concepts and notation 8. Explore a variety of various mathematical structures by focusing on mathematical objects,

operations, and resulting properties 9. Develop formal logical reasoning techniques and notation 10. Demonstrate the application of logic to analyzing and writing proofs 11. Develop techniques for counting, permutations and combinations 12. Develop the concept of relation through various representations (digraphs, matrices, lists).


5. Construct proofs using direct proof, proof by contraposition, proof by contradiction, proof by cases 6. Construct mathematical arguments using logical connectives and quantifiers and verify the correctness of an

argument using propositional and predicate logic and truth tables. 7. Demonstrate the ability to solve problems using counting techniques and combinatory in the context of discrete

probability. 8. Solve problems involving recurrence relations and generating functions.


= 12 INTRODUCTION & NUMBER THEORY

Services, Mechanisms and attacks-the Encryption techniques (Symmetric cipher model, substitution techniques, transposition techniques, steganography)..


BLOCK CIPHERS & PUBLIC KEY CRYPTOGRAPHY

Data Encryption Standard-Block cipher principles-block cipher modes of operation-Advanced Encryption Standard (AES)-Triple DES algorithm. Public key cryptography: Principles of public key cryptosystems-The RSA algorithm-Key management - Diffie Hellman Key exchange Unit - 3 Number of lectures

= 10 SECURITY PRACTICE & SYSTEM SECURITY

Web Security-: Application security (Database, E-mail and Internet), Data Security Considerations-Backups, Archival Storage and Disposal of Data, Security Technology-Firewall and VPNs, Intrusion Detection, Access Control.

Security Threats -Viruses, Worms, Trojan Horse, Bombs, Trapdoors, Spoofs, E-mail viruses, Macro viruses, Malicious Software, Network and Denial of Services Attack, Security Threats to E-Commerce-Electronic Payment System, e-Cash, Credit/Debit Cards, Hash Function and Digital Signature Unit - 4 Number of lectures

= 10 E-MAIL, IP Security

E-mail Security: Security Services for E-mail-attacks possible through E-mail - establishing keys privacy-authentication of the source-Message Integrity-Non-repudiation-Pretty Good Privacy-S/MIME.

IPSecurity: Overview of IPSec - IP and IPv6-Authentication Header-Encapsulation Security Payload (ESP)-Internet Key Exchange (Phases of IKE, ISAKMP/IKE Encoding).




6. 7. 8. 9. 10.

SEMESTER VI

Java

1. Name of the Department CSE 2. Course Name Java L T P 3. Course Code 13020670 3 0 2 4. Type of Course (use tick mark) Core (√ ) PE() OE() 5. Pre-requisite (if

any) C++ 6. Frequency (use tick

marks) Even (√)


Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28 8. Brief Syllabus Unit I: CORE JAVA Introduction to Java, Data types, variables, operators, Arrays, Control Statements, Classes & Methods, Inheritance, Exception Handling, Multithreading, Collections, I/O streams. Unit II: NETWORKING Connecting to a Server, Implementing Servers, Sending E-Mail, Making URL Connections, Advanced Socket Programming DATABASE NETWORKING: The Design of JDBC. The Structured Query Language, JDBC Installation, Basic JDBC Programming Concepts, Query Execution, Scrollable and Updatable Result Sets, Metadata, Row Sets, Transactions. Unit III: AWT and SWING Lists, Trees, Tables, Styled Text Components, Progress Indicators, Component Organizers The Rendering Pipeline, Shapes, Areas, Strokes, Paint, Coordinate Transformations, Clipping, Transparency and Composition, Rendering Hints, Readers and Writers for Images, Image Manipulation, Printing. The Clipboard, Drag and Drop. Unit IV: JAVABEANS COMPONENTS Beans, The Bean-Writing Process, Using Beans to Build an Application, Naming Patterns for Bean, Components and Events Bean Property, Tubes Bean info Classes, Property, Editors, Customizes. Unit V: JSP and SERVLETS Introduction to JSP, JSP built in objects, tags, Servlets, mapping, a web application. 9. Learning objectives: The objective of this course is to:

1. Introduce Java as a programming language. 2. Introduce Java as a dynamic web programming language. 3. Develop applications using Java. 4. Introduce the concepts of JDBC for the purpose of database connectivity. 5. Describe the technique to develop networking or socket programming.

10. Course Outcomes: On completion of this course, the students will be able to

viii) Design a desktop application which can be used by clients ix) Design a web application which can work as a dynamic web with the help of JDBC x) Develop an application which can also be connected with the database xi) Understand the concepts of Networking and Multi-threading


= 10 Title of the unit: CORE JAVA

Introduction to Java, Data types, variables, operators, Arrays, Control Statements, Classes & Methods, Inheritance, Exception Handling, Multithreading, Collections, I/O streams. Unit - 2 Number of lectures

= 8 Title of the unit: NETWORKING

Connecting to a Server, Implementing Servers, Sending E-Mail, Making URL Connections, Advanced Socket Programming DATABASE NETWORKING: The Design of JDBC. The Structured Query Language, JDBC Installation, Basic JDBC Programming Concepts, Query Execution, Scrollable and Updatable Result Sets, Metadata, Row Sets, Transactions.


= 8 Title of the unit: AWT & SWING

Lists, Trees, Tables, Styled Text Components, Progress Indicators, Component Organizers The Rendering Pipeline, Shapes, Areas, Strokes, Paint, Coordinate Transformations, Clipping, Transparency and Composition, Rendering Hints, Readers and Writers for Images, Image Manipulation, Printing. The Clipboard, Drag and Drop. Unit - 4 Number of lectures

= 8 Title of the unit: JAVA BEANS COMPONENTS

Beans, The Bean-Writing Process, Using Beans to Build an Application, Naming Patterns for Bean, Components and Events Bean Property, Tubes Bean info Classes, Property, Editors, Customizes. Unit - 5 Number of lectures

= 8 Title of the unit: JSP AND SERVLETS

Introduction to JSP, JSP built in objects, tags, Servlets, mapping, a web application. 12. Brief Description of self learning / E-learning component Online Video Lectures on advanced Java. Online video lectures on Data Base Connectivity. Practice of SQL Queries for Connectivity. ebooks available online:- iiti.ac.in/people/~tanimad/JavaTheCompleteReference.pdf Online tutorials and pdf files :- www.enos.itcollege.ee/~jpoial/allalaadimised/lugemist/Advanced-java.pdf 13. Books Recommended (3 Text Books + 2-3 Reference Books) xvi) Core JavaTM 2, Volume II-Advanced Features, 7th Edition by Cay Horetmann,Gary Cornelll Pearson

Publisher, 2004 xvii) Professional Java Programming by Brett Spell, WROX Publication xviii) Advanced Java 2 Platform, How to Program, 2nd Edition, Harvey. M. Dietal, Prentice Hall. xix) Advanced Java, Gajendra Gupta , Firewall Media. xx) Java: The Complete Reference by Herbert Schildt


Sr. No. Title CO covered 1 JDBC Installation (iii) 2 Exception Handling (i) 3 Introduction to AWT (ii) 4 Using Beans to Build an Application (iv) 5 Introduction to JSP (iii) 6 Designing of a web application (iii) 7 Learn Database Connectivity (iii) 15. Lab component components

Sr. No. Title CO covered 1 Program in java to sort an array using java. (i) 2 Create a program in java to read data from the user through I/O streams. (i) 3 Create a program in java to handle exceptions (iv) 4 Create a program to in java to implement threads. (iv) 5 Create a program in java to transfer data of a file to another file (ii) 6 Create a desktop application using AWT and SWING (ii) 7 Create a desktop application which uses JDBC (iii) 8 Create a static web using java concepts (iii) 9 Create a dynamic web using java concepts (iii) 10 Create a dynamic web using JSP, Servlets, JDBC (iii)

SEMESTER VI

Artificial Intelligence

1. Name of the Department: CSE 2. Course Name Artificial

Intelligence L T P

3. Course Code 13020671 3 0 2 4. Type of Course (use tick mark) Core (√) PE() OE() 5. Pre-requisite (if

any) C++ 6. Frequency (use tick

marks) Even (√)


Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28 8. Brief Syllabus: Unit I: Introduction Introduction to Artificial Intelligence, Foundations and History of Artificial Intelligence, Applications of Artificial Intelligence, Intelligent Agents, Structure of Intelligent Agents. Computer vision, Natural Language Possessing. Unit II: Introduction to Search Searching for solutions, Uniformed search strategies, Informed search strategies, Local search algorithms and optimistic problems, Adversarial Search, Search for games, Alpha - Beta pruning. Unit III: Knowledge Representation & Reasoning Propositional logic, Theory of first order logic, Inference in First order logic, Forward & Backward chaining, Resolution, Probabilistic reasoning, Utility theory, Hidden Markov Models (HMM), Bayesian Networks. Unit IV: Machine Learning Supervised and unsupervised learning, Decision trees, Statistical learning models, Learning with complete data - Naive Bayes models, Learning with hidden data – EM algorithm, Reinforcement learning. Unit V: Pattern Recognition Introduction, Design principles of pattern recognition system, Statistical Pattern recognition, Parameter estimation methods - Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA), Classification Techniques – Nearest Neighbour (NN) Rule, Bayes Classifier, Support Vector Machine (SVM), K – means clustering. 9. Learning objectives:

1. learn and possess a firm grounding in the existing techniques and component areas of Artificial Intelligence 2. apply this knowledge to the development of Artificial Intelligent Systems and to the exploration of research

problems. 10. Course Outcomes:

1. understand the principles of problem solving and be able to apply them successfully 2. be familiar with techniques for computer-based representation and manipulation of complex information,

knowledge, and uncertainty 3. gain awareness of several advanced AI applications and topics such as intelligent agents, planning and

scheduling, ma-chine learning, etc. 4. understand the principles of problem solving and be able to apply them successfully


= 10 Introduction

Introduction to Artificial Intelligence, Foundations and History of Artificial Intelligence, Applications of Artificial Intelligence, Intelligent Agents, Structure of Intelligent Agents. Computer vision, Natural Language Possessing. Unit - 2 Number of lectures

= 7 Introduction to Search

Searching for solutions, Uniformed search strategies, Informed search strategies, Local search algorithms and optimistic problems, Adversarial Search, Search for games, Alpha - Beta pruning. Unit - 3 Number of lectures

= 7 Knowledge Representation & Reasoning

Propositional logic, Theory of first order logic, Inference in First order logic, Forward & Backward chaining, Resolution, Probabilistic reasoning, Utility theory, Hidden Markov Models (HMM), Bayesian Networks. Unit - 4 Number of lectures

= 7 Machine Learning

Supervised and unsupervised learning, Decision trees, Statistical learning models, Learning with complete data - Naive Bayes models, Learning with hidden data – EM algorithm, Reinforcement learning. Unit - 5 Number of lectures

= 7 Pattern Recognition

Introduction, Design principles of pattern recognition system, Statistical Pattern recognition, Parameter estimation methods - Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA), Classification Techniques – Nearest Neighbour (NN) Rule, Bayes Classifier, Support Vector Machine (SVM), K – means clustering. 12. Brief Description of self learning / E-learning component. This learning method gives students to find out their learning capability. Students involve some sort of choice in



1. Artificial Intelligence – A Modern Approach - Stuart Russell and Peter Norvig, Pearson Education. 2. Artificial Intelligence - Elaine Rich and Kevin Knight, McGraw-Hill 3. Introduction to Artificial Intelligence - E Charniak and D McDermott, Pearson Education 4. Artificial Intelligence and Expert Systems - Dan W. Patterson, Prentice Hall of India

Sr. No. Title CO covered 1 . Study of PROLOG.

Write the following programs using PROLOG.

2 Write a program to solve 8 queens problem.

3 Solve any problem using depth first search.

4 Solve any problem using best first search.

5 Solve 8-puzzle problem using best first search

6 Solve Robot (traversal) problem using means End Analysis.

7 Solve traveling salesman problem.

SEMESTER VI

Wireless and Mobile Communication

1. Name of the Department CSE 2. Course Name Wireless and

Mobile Communication

L T P

3. Course Code 13020611 3 0 0

4. Type of Course (use tick mark) Core () PE(√ ) OE()


Computer Networks 6. Frequency (use tick marks)

Even (√)


Every Sem ()


8. Brief Syllabus Unit I: INTRODUCTION TO WIRELESS COMMUNICATIONS

History and evolution of mobile radio systems. Types of mobile wireless services/systems-Cellular, WLL, Paging, Satellite systems, Standards, Future trends in personal wireless systems.

Unit II: CELLULAR CONCEPTS AND SYSTEM DESIGN FUNDAMENTALS

Cellular concept and frequency reuse, Multiple Access Schemes, channel assignment and handoff, Interference and system capacity, Trunking and Erlang capacity calculations.

Unit III: MOBILE RADIO PROPAGATION MODELS

Radio wave propagation issues in personal wireless systems, Propagation models, Multipath fading and Base band impulse respond models, parameters of mobile multipath channels, Antenna systems in mobile radio.

Unit IV: MODULATION TECHNIQUES

Overview analog and digital modulation techniques, Performance of various modulation techniques-Spectral efficiency, Error-rate, Power Amplification, Equalizing Rake receiver concepts, Diversity and space-time processing, Speech coding and channel coding.

Unit V: SYSTEM EXAMPLES AND DESIGN ISSUES

Multiple Access Techniques-FDMA, TDMA and CDMA systems, operational systems, Wireless networking, design issues in per-sonal wireless systems

9. Learning objectives: The objective of this course is to:

1. Introduce of wireless communication and mobile communication standards. 2. Provide understanding of advanced multiple access techniques, Mobile radio Propagation Models and

modulation tech-niques 3. Provide understanding of digital cellular systems (GSM, CDMA, GPRS, W-CDMA etc.)


1. Understand principles of wireless communication and, various mobile network architecture. 2. Understand various Modulation techniques for Mobile Radio. 3. Understand the information theoretical aspects (such as the capacity) of wireless channels 4. Realize various wireless and mobile cellular communication systems 5. Implement practical mobile applications


= 10 Title of the unit:INTRODUCTION TO WIRELESS COMMUNICATIONS

History and evolution of mobile radio systems. Types of mobile wireless services/systems-Cellular, WLL, Paging, Satellite systems, Standards, Future trends in personal wireless systems.

Unit - 2 Number of lectures =8

Title of the unit:CELLULAR CONCEPTS AND SYSTEM DESIGN FUNDAMENTALS

Cellular concept and frequency reuse, Multiple Access Schemes, channel assignment and handoff, Interference and system capacity, Trunking and Erlang capacity calculations.


Title of the unit: MOBILE RADIO PROPAGATION MODELS

Radio wave propagation issues in personal wireless systems, Propagation models, Multipath fading and Base band impulse respond models, parameters of mobile multipath channels, Antenna systems in mobile radio.


Title of the unit: MODULATION TECHNIQUES

Overview analog and digital modulation techniques, Performance of various modulation techniques-Spectral efficiency, Error-rate, Power Amplification, Equalizing Rake receiver concepts, Diversity and space-time processing, Speech coding and channel coding.


Title of the unit: SYSTEM EXAMPLES AND DESIGN ISSUES

Multiple Access Techniques-FDMA, TDMA and CDMA systems, operational systems, Wireless networking, design issues in per-sonal wireless systems

12. Brief Description In this course, students examine fundamental concepts of mobile cellular communications and specifics of current and proposed U.S. cellular systems. Topics include frequency reuse, call processing, propagation loss, multipath fading and methods of reducing fades, error correction requirements and techniques, modulation methods: FDMA, TDMA,

and CDMA techniques, microcell issues, mobile satellite systems and IMT-2000

13. Books Recommended (2 Text Books + 2 Reference Books) i) T. S. Rappaport, Wireless digital communications; Principles and practice, Prentice Hall, NJ, 1996. ii) Schiller, Mobile Communications; Pearson Education Asia Ltd., 2000 iii) K. Feher, Wireless digital communications, PHI, New Delhi, 1999. iv) W. C. Y. Lee, Mobile communications engineering: Theory and Applications, Second Edition, McGraw Hill,

New York.1998.

SEMESTER VI

Distributed System

1. Name of the Department: CSE 2. Course Name Distributed system L T P 3. Course Code 13020610 3 0 2 4. Type of Course (use tick mark) Core () PE(√) OE() 5. Pre-requisite (if

any) DWDM,O.S 6. Frequency (use tick

marks) Even (√)


Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 28 8. Brief Syllabus COURSE CONTENT Unit I: Introduction Definition - Evolution- Goals of distributed systems, system models- Issues in the design of distributed systems- Distributed com-puting environment Unit II: COMMUNICATION Message Passing – Features and Issues -Synchronization-Buffering - Process Addressing - Failure Handling - Remote procedure call (RPC): Model – Implementation - Stub generation - RPC messages – Marshaling - server Management - Call semantics - communication protocols for RPC-Client server binding – RMI. Unit III : DISTRIBUTED SHARED MEMORY Distributed shared memory- Design and implementation issues- Sequential consistency - Release consistency, Process migration Features & Mechanism Unit IV:SYNCHRONIZATION Synchronizing physical clocks - Logical clocks - Distributed coordination – Event Ordering – Mutual Exclusion – Deadlock - Elec-tion algorithms Unit V :DISTRIBUTED FILE SYSTEMS Introduction – File Models – File accessing, sharing and caching - File Replication – Atomic transactions Case Study HADOOP. : Resource and process management - Task assignment approach - Load balancing approach - Load sharing approach 9. Learning objectives:

1. Familiarize the students with the basics of distributed computing systems. 2. To introduce the concepts of distributed file systems, shared memory and message passing systems,

synchronization and resource management.

10. Course Outcomes: 1. Verify and analyze the time complexity of the algorithms related to distributed computing. 2. Design and develop various algorithms for problems in distributed computing 3. Compare various resource allocation stratagies.




Definition - Evolution- Goals of distributed systems, system models- Issues in the design of distributed systems- Distributed com-puting environment Unit - 2 Number of lectures

=8 Title of the unit: COMMUNICATION

Message Passing – Features and Issues -Synchronization-Buffering - Process Addressing - Failure Handling - Remote procedure call (RPC): Model – Implementation - Stub generation - RPC messages – Marshaling - server Management -

Call semantics - communication protocols for RPC-Client server binding – RMI. Unit - 3 Number of lectures

= 8 Title of the unit: DISTRIBUTED SHARED MEMORY

Distributed shared memory- Design and implementation issues- Sequential consistency - Release consistency, Process migration Features & Mechanism Unit - 4 Number of lectures

= 10 Title of the unit: SYNCHRONIZATION

Synchronizing physical clocks - Logical clocks - Distributed coordination – Event Ordering – Mutual Exclusion – Deadlock - Elec-tion algorithms. Unit - 5 Number of lectures

= 8 Title of the unit: DISTRIBUTED FILE SYSTEMS

Introduction – File Models – File accessing, sharing and caching - File Replication – Atomic transactions Case Study HADOOP. : Resource and process management - Task assignment approach - Load balancing approach - Load sharing approach 12. Brief Description of self learning / E-learning component Online Video Lectures of DOS 13. Books Recommended (1Text Books + 4 Reference Books)

1. George Colouris, Jean Dollimore and Tim Kindberg, “Distributed Systems – Concepts and Design”, Pearson Education Private Limited, New Delhi, 2001

REFERENCE BOOKS 1. Gerard Tel, “Introduction to Distributed algorithms”, Cambridge University Press, USA, 2000.

2. Andrzej Goscinski, “Distributed Operating Systems, the logical Design”, Addison Wesley

Publishing Company, USA, 1991.

3. Tanenbaum, “Modern Operating Systems”, Prentice Hall of India, New Delhi, 1999.


Sr. No. Title CO covered 1 Introduction (i) 2 COmmunication (ii) 3 DISTRIBUTED SHARED MEMORY (iii) 4 SYNCHRONIZATION (iii) 5 DISTRIBUTED FILE SYSTEMS (iv) & (v)

SEMESTER VI

Data Warehouse and Data Mining

1. Name of the Department: CSE 2. Course Name Data Warehouse

and Data Mining L T P

3. Course Code 13020672 3 0 0 4. Type of Course (use tick mark) Core () PE(√) OE() 5. Pre-requisite (if

any) DBMS 6. Frequency (use tick

marks) Even (√)


Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus: Unit I Overview, Motivation (for Data Mining),Data Mining-Definition & Functionalities, Data Processing, Form of Data Preprocess-ing, Data Cleaning: Missing Values, Noisy Data, (Binning,Clustering, Regression, Computer and Human inspection),Inconsistent Data, Data Integration and Transformation. Data Reduction:-Data Cube Aggregation, Dimensionality reduction, Data 35 Com-pression, Numerosity Reduction, Clustering, Discretization and Concept hierarchy generation Unit II Concept Description:- Definition, Data Generalization, Analytical Characterization, Analysis of attribute relevance, Mining Class comparisions, Statistical measures in large Databases. Measuring Central Tendency, Measuring Dispersion of Data, Graph Dis-plays of Basic Statistical class Description, Mining Association Rules in Large Databases, Association rule mining,mining Single-Dimensional Boolean Association rules from Transactional Databases– Apriori Algorithm, Mining Multilevel Association rules from Transaction Databases and Mining Multi-Dimensional Association rules from Relational Databases Unit III Classification and Predictions: What is Classification & Prediction, Issues regarding Classification and prediction, Decision tree, Bayesian Classification, Classification by Back propagation, Multilayer feed-forward Neural Network, Back propagation Algo-rithm, Classification methods K-nearest neighbor classifiers, Genetic Algorithm. Cluster Analysis: Data types in cluster analysis, Categories of clustering methods, Partitioning methods. Hierarchical Clustering- CURE and Chameleon, Density Based Methods-DBSCAN, OPTICS, Grid Based Methods- STING, CLIQUE, Model Based Method –Statistical Approach, Neural Network approach, Outlier Analysis Unit IV Data Warehousing: Overview, Definition, Delivery Process, Difference between Database System and Data Warehouse, Multi Dimensional Data Model, Data Cubes, Stars, Snow Flakes, Fact Constellations, Concept hierarchy, Process Architecture, 3 Tier Architecture, Data Marting. Unit V Aggregation, Historical information, Query Facility, OLAP function and Tools. OLAP Servers, ROLAP, MOLAP, HOLAP, Data Mining interface, Security, Backup and Recovery, Tuning Data Warehouse, Testing Data Warehouse. 9. Learning objectives:

6. Introduce data mining principles and techniques. 7. Introduce data mining as a cutting edge business intellegence tool. 8. Develop and apply critical thinking, problem solving and decision making skills. 9. Introduce the concepts of Data Warehousing, difference between database and data warehousing. 10. Describe and demonstrate basic data mining algorithms, methods, tools, 11. Describe ETL Model and the Star Schema to design a Data Warehouse.


1. Design a data warehouse or data mart to present information needed by the and can be utilized for managing clients.

2. Design and implement a quality data warehouse or data mart effectively and administer the data resources in such a way that it will truly meet management’s requirements.

3. Evaluate standards and new technologies to determine their potential impact on your information resource for a large complex data warehouse/data mart.

4. Use data mining tools for projects and to build reliable products as per demand.


= 10

Overview, Motivation(for Data Mining),Data Mining-Definition & Functionalities, Data Processing, Form of Data Preprocess-ing, Data Cleaning: Missing Values, Noisy Data, (Binning,Clustering, Regression, Computer and Human inspection),Inconsistent Data, Data Integration and Transformation. Data Reduction:-Data Cube Aggregation, Dimensionality reduction, Data 35 Com-pression, Numerosity Reduction, Clustering, Discretization and Concept hierarchy generation Unit - 2 Number of lectures

= 8

Concept Description:- Definition, Data Generalization, Analytical Characterization, Analysis of attribute relevance, Mining Class comparisons, Statistical measures in large Databases. Measuring Central Tendency, Measuring Dispersion of Data, Graph Dis-plays of Basic Statistical class Description, Mining Association Rules in Large Databases, Association rule mining,mining Single-Dimensional Boolean Association rules from Transactional Databases– Apriori Algorithm, Mining Multilevel Association rules from Transaction Databases and Mining Multi-Dimensional Association rules from Relational Databases Unit - 3 Number of lectures

= 8

Classification and Predictions: What is Classification & Prediction, Issues regarding Classification and prediction, Decision tree, Bayesian Classification, Classification by Back propagation, Multilayer feed-forward Neural Network, Back propagation Algo-rithm, Classification methods K-nearest neighbor classifiers, Genetic Algorithm. Cluster Analysis: Data types in cluster analysis, Categories of clustering methods, Partitioning methods. Hierarchical Clustering- CURE and Chameleon, Density Based Methods-DBSCAN, OPTICS, Grid Based Methods- STING, CLIQUE, Model Based Method –Statistical Approach, Neural Network approach, Outlier Analysis Unit - 4 Number of lectures

= 8

Data Warehousing: Overview, Definition, Delivery Process, Difference between Database System and Data Warehouse, Multi Dimensional Data Model, Data Cubes, Stars, Snow Flakes, Fact Constellations, Concept hierarchy, Process Architecture, 3 Tier Architecture, Data Marting. Unit - 5 Number of lectures

= 8

Aggregation, Historical information, Query Facility, OLAP function and Tools. OLAP Servers, ROLAP, MOLAP, HOLAP, Data Mining interface, Security, Backup and Recovery, Tuning Data Warehouse, Testing Data Warehouse. 12. Brief Description of self learning / E-learning component. This learning method gives students to find out their learning capability. Students involve some sort of choice in



1. M.H.Dunham,”Data Mining:Introductory and Advanced Topics” Pearson Education. 2. Sam Anahory, Dennis Murray, “Data Warehousing in the Real World: A Practical Guide for Building Decision

Support Systems, Pearson Education. 3. Jiawei Han, Micheline Kamber,”Data Mining Concepts & Techniques” Elsevier. 4. Mallach,”Data Warehousing System”,McGraw –Hill.

B.Tech-Computer Science & Engineering SEMESTER VII Web Technology

1. Name of the Department: CSE 2. Course Name Web Technology L-3 T-0 P-2 3. Course Code 13020773 4. Type of Course (use tick mark) Core (√) PE() OE() 5. Pre-requisite (if



Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 38 Tutorials = Practical = 12 8. Brief Syllabus: UNIT - I

HTML & STYLE SHEETS:- Basics of HTML, formatting and fonts, commenting code, color, hyperlink, lists, tables, images, forms, XHTML, Meta tags, Character entities, frames and frame sets, Browser architecture and Web site structure. Overview and features of HTML5 Style sheets : Need for CSS, introduction to CSS, basic syntax and structure, using CSS, background images, colors and properties, manipulating texts, using fonts, borders and boxes, margins, padding lists, positioning using CSS, CSS2,

UNIT - II

HTML5 & CSS3:

HTML5: Introduction and Semantic, Form,-Canvas SVG, Audio and Video,-Drag and Drop, Web Storage ,Geo Location, Application Cache

CSS3: Introduction and Selectors, Borders, Backgrounds, Text Fonts, Transitions, Animations

UNIT – III

Java Script:- Introduction, Client-Side JavaScript, Server-Side JavaScript, JavaScript Objects, JavaScript Security, Operators, Statements, Document and its associated objects, Events and Event Handlers, Core JavaScript (Properties and Methods of Each)

UNIT – IV

PHP (Hypertext Preprocessor): Introduction, syntax, variables, strings, operators, if-else, loop, switch, array, function, form, mail, file upload, session, error, exception, filter, PHP-ODBC.


To enhance problem solving skills of engineering students using a powerful problem solving tool namely numerical methods. The tool is capable of handling large systems of equations, nonlinearities and complicated geometries that are common in engineering practice but often impossible to solve analytically.


5) Apply various numerical methods and appreciate a trade off in using them. 6) Understand the source of various types of errors and their effect in using these methods. 7) To distinguish between Numerical and Analytical methods along with their Merits and demerits.

8) Understand the use of digital computers in implementation of these methods.


= 12 HTML & STYLE SHEETS

Basics of HTML, formatting and fonts, commenting code, color, hyperlink, lists, tables, images, forms, XHTML, Meta tags, Character entities, frames and frame sets, Browser architecture and Web site structure. Overview and features of HTML5 Style sheets : Need for CSS, introduction to CSS, basic syntax and structure, using CSS, background images, colors and properties, manipulating texts, using fonts, borders and boxes, margins, padding lists, positioning using CSS, CSS2, Overview and features of CSS3


HTML5 & CSS3:

HTML5: Introduction and Semantic, Form,-Canvas SVG, Audio and Video,-Drag and Drop, Web Storage ,Geo Location, Application Cache

CSS3: Introduction and Selectors, Borders, Backgrounds, Text Fonts, Transitions, Animations


= 10 PHP (Hypertext Preprocessor):

Java Script:- Introduction, Client-Side JavaScript, Server-Side JavaScript, JavaScript Objects, JavaScript Security, Operators, Statements, Document and its associated objects, Events and Event Handlers, Core JavaScript (Properties and Methods of Each).


HTML & STYLE SHEETS

PHP (Hypertext Preprocessor): Introduction, syntax, variables, strings, operators, if-else, loop, switch, array, function, form, mail, file upload, session, error, exception, filter, PHP-ODBC 12. Brief Description of self learning / E-learning component. This learning method gives students to find out their learning capability. Students involve some sort of choice in


13. Books Recommended (1 Text Book + 2 Reference Books) 1. Ullman, “PHP for the Web: Visual QuickStart Guide”, Pearson Education

2. PHPMYSQL F undamental learning Book, Kent Elchuk

3. Beginning HTML5 with CSS3, Apress publisher

4. Charlie Collins, Michael Galpin and Matthias Kappler, “Android in Practice”, DreamTech

17. Lab components

Sr. No. Title CO covered 1 eate a Web Page using basic tags in html 5 1 2 rite a program to create all types of list in HTML 3 3 eate a table using Html 5 and CSS 3 4 Write a program using labels, radio buttons, and submit buttons 3

5 Create a simple webpage using HTML 3 6 Use frames to Include Images and Videos. 3 7 Add a Cascading Style sheet for designing the web page. 3 8 Design a web page with validation using JavaScript.

3

9 ow to make all fields of a form mandatory in java script 3 10 eate a registration form and validate it using java script 3 Write a program to maintain session in PHP 11 Perform data base connectivity in PHP 3 12 eate a dynamic web page using PHP 3

1. Name of the Department : Computer Science Engineering 2. Course

Name Soft Computing

L T P

3. Course Code 3 0 0 4. Type of Course (use tick

mark) Core PE() OE()


CN 6. Frequency (use tick marks)

Even Odd () Either Sem ()

Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus Unit I: Artificial Neural Networks Basic-concepts-single layer perception-Multi layer perception-Supervised and unsupervised learning back propagation networks, Application.

Unit II: Fuzzy Systems Fuzzy sets and Fuzzy reasoning-Fuzzy matrices-Fuzzy functions-decomposition-Fuzzy automata and languages- Fuzzy control methods-Fuzzy decision making, Applications.

Unit III: Neuro-Fuzzy Modeling Adaptive networks based Fuzzy interfaces-Classification and Representation trees-Data dustemp algorithm –Rule base structure identification-Neuro-Fuzzy controls

Unit IV: Genetic Algorithm Survival of the fittest-pictures computations-cross over mutation-reproduction-rank method-rank space method, Application.

Unit V: Artificial Intelligence AI Search algorithm-Predicate calculus rules of interface – Semantic networks-frames-objects-Hybrid models, applications.

TEXT BOOKS

9. Learning objectives: The objective of this course is to

1. familiarize with soft computing concepts 2. introduce and use the idea of Neural networks, fuzzy logic and use of heuristics based on human

experience 3. introduce and use the concepts of Genetic algorithm and its applications to soft computing using some

applications. 10. Course Outcomes: On completion of this course, the students will be able to:- 1. Identify and describe soft computing techniques and their roles in building intelligent machines 2. Recognize the feasibility of applying a soft computing methodology for a particular problem

3. Apply fuzzy logic and reasoning to handle uncertainty and solve engineering problems, genetic algorithms to combinatorial optimization problems and neural networks to pattern classification and regression problems

11. Unit wise detailed content Unit-1 Number of

lectures = 10 Title of the unit: Artificial Neural Network

Basic-concepts-single layer perception-Multi layer perception-Supervised and unsupervised learning back propagation networks, Application Unit - 2 Number of

lectures = 8 Title of the unit: Fuzzy System

Fuzzy sets and Fuzzy reasoning-Fuzzy matrices-Fuzzy functions-decomposition-Fuzzy automata and languages- Fuzzy control methods-Fuzzy decision making, Applications Unit - 3 Number of

lectures = 8 Title of the unit: Neuro Fuzzy Modeling

Adaptive networks based Fuzzy interfaces-Classification and Representation trees-Data dustemp algorithm –Rule base structure identification-Neuro-Fuzzy controls

Unit - 4 Number of

lectures = 8 Title of the unit: Genetic Algorithm

Survival of the fittest-pictures computations-cross over mutation-reproduction-rank method-rank space method, Application Unit - 5 Number of

lectures = 8 Title of the unit: Artificial Intelligence

AI Search algorithm-Predicate calculus rules of interface – Semantic networks-frames-objects-Hybrid models, applications.

12. Brief Description of self learning / E-learning component

13. Books Recommended (3 Text Books + 2-3 Reference Books) 1. E – Neuro Fuzzy and Soft computing – Jang J.S.R., Sun C.T and Mizutami, Prentice hall New Jersey,

1998

2. Fuzzy Logic Engineering Applications – Timothy J.Ross, McGraw Hill, NewYork, 1997.

3. Fundamentals of Neural Networks – Laurene Fauseett, Prentice Hall India, New Delhi, 1994. 4. Introduction to Artificial Intelligence – E Charniak and D McDermott, Pearson Education

5. Artificial Intelligence and Expert Systems – Dan W. Patterson, Prentice Hall of India.

Lab components

Sr. No. Title CO covered 1 Study of Matlab 2 (a) Write a program to perform basic operations in Matlab (b) To perform matrix operations in Matlab 3 (a) Introduction to script file in Matlab (b) Write a program to calculate the factorial of a number by creating a script

file by using while loop

(c) Write a program in Matlab to find the factorial by creating a function file by using for loop

4 (a) Write a program in Matlab to plot multiple curves in single plot by creating a script file (b) Write a program in Matlab for plotting multiple curves in single figure

5 (a) Write a program in Matlab to plot Activation function used in neural network

(b) Write a program in Matlab to plot piecewise continuous activation function (threshold and signum function in neural network)

6 (a) To realize gates using Mcculloh Pitt model in Matlab (b) Write a program to implement XOR gate using Mcclloh-Pitts neuron 7 (a) Write a program to create the Perceptron using GUI in Matlab (b) Write a program in Matlab to create `Perceptron using commands 8 9

(a) Write a program in Matlab to classify the Classes using Perceptron (b) Write a program in Matlab for Pattern Classification using Perceptron network Write a program in Matlab for creating a Back Propagation Feed-forward neural network

10 To design a Hopfield Network which stores 4 vectors

11 Write a program to illustrate how the perception learning rule works for non-linearly separable problems

12 Write a program to illustrate Linearly non-separable vectors

SEMESTER VII Human Value & Professional Ethics

1. Name of the Department- Mechanical Engineering/ Computer Science Engineering/ Civil Engineering/ Electronics & Communication Engineering

2. Course Name Human Values & Professional Ethics

L T C

3. Course Code 13020772 2 0 0 4. Type of Course (use tick mark) Core () PE() OE() 5. Pre-requisite (if

any) Adaptive 6. Frequency (use tick


Sem ()

EverySem ()

7. Total Number of Lectures, Tutorials, Practical Lectures =28 Tutorials = 0 Practical = 0 8. Brief Syllabus The methodology of this course is universally adaptable, involving a systematic, rational study of the human being and Inter-relationship of technology growth and social, economic and cultural growth. It is free from any dogma or value prescriptions. This process of self-exploration takes the form of a dialogue between the teacher and the students to begin with and within the student himself/herself finally. 9. Learning objectives: This introductory course input is intended. a. To help the students appreciate the essential complementarily between 'VALUES' and 'SKILLS' to ensure sustained happiness and prosperity which are the core aspirations of all human beings. b. To facilitate the development of a Holistic perspective among students towards life, profession and happiness, based on a correct understanding of the Human reality and the rest of existence. Such a holistic perspective forms the basis of Value based living in a natural way. c. To highlight plausible implications of such a Holistic understanding in terms of ethical human conduct, trustful and mutually satisfying human behaviour and mutually enriching interaction with Nature. 10. Course Outcomes (COs):

On completion of this course, the students will be able to 1. Understand the significance of value inputs in a classroom and start applying them in their professional life. 2. Understand the role of a human being in ensuring harmony in society and nature. 3. Distinguish between ethical and unethical practices, and start working out the strategy to actualize a harmonious environment wherever they work. 11. Unit wise detailed content Unit-1 Number of

lectures = 6 Title of the unit: Introduction to Human Values

Course Introduction - Need, basic Guidelines, Content and Process for Value Education: Understanding the need, basic guidelines, content and process for Value Education. Self Exploration - what is it? - its content and process; 'Natural Acceptance' and Experiential Validation - as the mechanism for self exploration. Continuous Happiness and Prosperity - A look at basic Human Aspirations. Right understanding, Relationship and Physical Facilities - the basic requirements for fulfillment of aspirations of every human being with their correct priority. Understanding Happiness and Prosperity correctly - A critical appraisal of the current scenario. Method to fulfill the above human aspirations: understanding and living in harmony at various levels. Unit – 2 Number of

lectures = 6 Title of the unit: Harmony in the Human Being .

Understanding Harmony in the Human Being - Harmony in Myself! : Understanding human being as a coexistence of the sentient 'I' and the material 'Body'. Understanding the needs of Self ('I') and 'Body' - Sukh and Suvidha. Understanding the Body as an instrument of 'I' ( I being the doer, seer and enjoyer). Understanding the harmony of I with the Body: Sanyam and Swasthya; correct appraisal of Physical needs, meaning of Prosperity in detail. Programs to ensure Sanyam and Swasthya


Title of the unit: Harmony in the Family and Society

Understanding Harmony in the Family and Society - Harmony in Human - Human Relationship: Understanding harmony in the Family the basic unit of human interaction. Understanding values in human - human relationship; meaning of Nyaya and program for its fulfillment to ensure Ubhaytripti; Trust (Vishwas) and Respect ( Samman) as the foundational values of relationship. Understanding the meaning of Vishwas; Difference between intention and competence. Understanding the meaning of Samman, Difference between respect and differentiation; the other salient values in relationship. Understanding the harmony in the society ( society being an extension of family): Samadhan, Samridhi, Abhay, Sah-astiva as comprehensive Human Goals. Visualizing a universal harmonious order in society - Undivided Society ( Akhand Samaj), Universal Order ( Sarvabhaum Vyawastha) - from family to world family! Unit – 4 Number of

lectures = 5 Title of the unit Harmony in the Nature

Understanding Harmony in the nature and Existence - Whole existence as Co-existence: Understanding the harmony in the Nature. Interconnectedness and mutual fulfillment among the four orders of nature - recyclability and self-regulation in nature. Understanding Existence as Co-existence (Sah-astiva) of mutually interacting units in all-pervasive space. Holistic perception of harmony at all levels of existence Unit – 5 Number of

lectures = 5 Title of the unit: Implication of Harmony on Professional Ethics

Implications of the above Holistic Understanding of Harmony on Professional Ethics: Natural acceptance of human values, Definitiveness of Ethical Human Conduct, Basic for Humanistic Education, Humanistic Constitution and Humanistic Universal Order. Competence in professional ethics: a. Ability to utilize the professional competence for augmenting universal human order, b. Ability to identify the scope and characteristics of people-friendly and eco-friendly production systems, c. Ability to identify and develop appropriate techologies and management patterns for above production systems. 12. Brief Description of self learning / E-learning component 13. Books Recommended (3 Text Books + 2-3 Reference Books)

TEXT BOOKS

1. R. R. Gaur, R Sangal, G P Bagaria, 2009, A Foundation Course in Human Values and Professional Ethics. 2. Prof. K. V. Subba Raju, 2013, Success Secrets for Engineering Students, Smart Student Publications, 3rd Edition.

REFERENCE BOOKS

1. Ivan IIIich, 1974, Energy & Equity, The Trinity Press, Worcester, and HarperCollins, USA 2. E. F. Schumancher, 1973, Small is Beautiful: a study of economics as if people mattered. Blond & Briggs, Britain. 3. A Nagraj, 1998 Jeevan Vidya ek Parichay, Divya Path Sansthan, Amarkantak. 4. Sussan George, 1976, How the Other Half Dies, Penguin Press, Reprinted 1986, 1991. 5. P. L. Dhar, R. R. Gaur, 1990, Science and Humanism, Commonwealth Publishers. 6. A. N. Tripathy, 2003, Human Values, New Age International Publishers. 7. Subhas Palekar, 2000, How to practice Natural Farming, Pracheen(Vaidik) Krishi Tantra Shodh, Amravati. 8. Donella H. Meadows, Dennis L. Meadows, Jorgen Randers, William W. Behrens III, 1972, Limits to Growth - Club of Rome's report, Universe Books. 9. E G Seebauer & Robert L.Berry, 2000, Fundamentals of Ethics for Scientists & Engineers, Oxford University Press.

SEMESTER VII Software Project Management

1. Name of the Department 2. Course Name Software project

management L T P

3. Course Code 13020710 3 0 0 4. Type of Course (use tick mark) Core ( ) PE(√) OE() 5. Pre-requisite (if



Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus COURSE CONTENT Unit I: Introduction Faults, Errors, and Failures, Basics of software testing, Testing objectives, Principles of testing, Requirements, behavior and cor-rectness, Testing and debugging, Test metrics and measurements, Verification, Validation and Testing, Types of testing, Software Quality and Reliability, Software defect tracking. Unit II: White Box and Black Box Testing White box testing, static testing, static analysis tools, Structural testing: Module/Code functional testing, Code coverage testing, Code complexity testing, Black Box testing, Requirements based testing, Boundary value analysis, Equivalence partitioning, state/ graph based testing, Model based testing and model checking, Differences between white box and Black box testing. Unit III: Integration, System, and Acceptance Testing Top down and Bottom up integration, Bi-directional integration, System integration, Scenario Testing, Defect Bash, Functional versus Non-functional testing, Design/Architecture verification, Deployment testing, Beta testing, Scalability testing, Reliability testing, Stress testing, Acceptance testing: Acceptance criteria, test cases selection and execution, Unit IV: Test Selection & Minimization for Regression Testing Regression testing, Regression test process, Initial Smoke or Sanity test, Selection of regression tests, Execution Trace, Dynamic Slicing, Test Minimization, Tools for regression testing, Ad hoc Testing: Pair testing, Exploratory testing, Iterative testing, Defect seeding. Unit V: Test Management and Automation Test Planning, Management, Execution and Reporting, Software Test Automation: Scope of automation, Design & Architecture for automation, Generic requirements for test tool framework, Test tool selection, Testing in Object Oriented Systems. 9. Learning objectives: The objective of this course is to

1. Presenting various techniques and strategies of software testing and inspection and pointing out the importance of testing in achieving high-quality software.

2. Understand concept of reliability and quality, the role it plays in software engineering, and how it is modeled and measured.

3. Showing how software product and process are managed and controlled for maintaining software quality assurance.

4. Highlighting importance of software maintenance, restructuring, and reengineering. 10. Course Outcomes:


1. Use the appropriate methods and tools for estimating software cost. 2. Understand the difference between different software design models and techniques and how to apply them. 3. Recognize the importance of software reliability and how we can design dependable software, and what measures

are used. 4. Understand the principles and techniques underlying the process of inspecting and testing software and making it

free of errors and tolerable. 5. Recognize the importance of software standards and quality assurance.

11. Unit wise detailed content Unit-1 Number of lectures Title of the unit: Introduction

= 10 Faults, Errors, and Failures, Basics of software testing, Testing objectives, Principles of testing, Requirements, behavior and correctness, Testing and debugging, Test metrics and measurements, Verification, Validation and Testing, Types of testing, Software Quality and Reliability, Software defect tracking. : Unit - 2 Number of lectures

= 8 Title of the unit: White Box and Black Box Testing

White box testing, static testing, static analysis tools, Structural testing: Module/Code functional testing, Code coverage testing, Code complexity testing, Black Box testing, Requirements based testing, Boundary value analysis, Equivalence partitioning, state/ graph based testing, Model based testing and model checking, Differences between white box and Black box testing. Unit - 3 Number of lectures

= 8 Title of the unit: Integration, System, and Acceptance Testing

Top down and Bottom up integration, Bi-directional integration, System integration, Scenario Testing, Defect Bash, Functional versus Non-functional testing, Design/Architecture verification, Deployment testing, Beta testing, Scalability testing, Reliability testing, Stress testing, Acceptance testing: Acceptance criteria, test cases selection and execution, . Unit - 4 Number of lectures

= 8 Title of the unit: Test Selection & Minimization for Regression Testing

Regression testing, Regression test process, Initial Smoke or Sanity test, Selection of regression tests, Execution Trace, Dynamic Slicing, Test Minimization, Tools for regression testing, Ad hoc Testing: Pair testing, Exploratory testing, Iterative testing, Defect seeding. Unit - 5 Number of lectures

= 8 Title of the unit: Test Management and Automation

Test Planning, Management, Execution and Reporting, Software Test Automation: Scope of automation, Design & Architecture for automation, Generic requirements for test tool framework, Test tool selection, Testing in Object Oriented Systems. 12. Brief Description of self learning / E-learning component Online Video Lectures on testing Practice on testing tools 13. Books Recommended (1Text Books + 4 Reference Books)

3. S. Desikan and G. Ramesh, “Software Testing: Principles and Practices”, Pearson Education. 4. Aditya P. Mathur, “Fundamentals of Software Testing”, Pearson Education.

REFERENCE BOOKS 1. Naik and Tripathy, “Software Testing and Quality Assurance”, Wiley .

SEMESTER VII Image Processing & Pattern Recognition

1. Name of the Department: FET 2. Course Name Image Processing &

Pattern Recognition L-3 T-0 P-0


any) C Language 6. Frequency (use tick


Sem() EverySem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus: Introduction to Image Processing, Image restoration, Image data compression, , Segmentation techniques, Shape analysis, topological and texture analysis. Pattern Recognition- Basics, Design Principles, Mathematical Foundation for Pattern Recognition system, Statistical Pattern recognition- Bayesian Decision Theory, Classifiers, Normal density and discriminant functions, parameters estimation methods, Hidden Markov Models, Gaussian mixture models. 9. Learning objectives: impart knowledge in the area of image and image processing. understand fundamentals of digital image processing, provide knowledge of the applications of the theories taught in Digital Image Processing. learn the fundamentals of Pattern recognition and to choose an appropriate feature . classification algorithm for a pattern recognition problems and apply them properly using modern computing tools such as Matlab, C/C++ etc 10. Course Outcomes:

iii. Understand Basics of Image formation and transformation using sampling and quantization iv. Understand different types of signal processing techniques used for image sharpening and smoothing

iii. Perform and apply compression and coding techniques used for image data. iv. Understand the nature and inherent difficulties of the pattern recognition problems.

v. Understand Concepts, trade-offs and appropriateness of the different types and classification techniques such as Bayesian, Maximum-likelihood,etc.


= 10 Title of the unit:Introduction to Image Processing

Image formation, image geometry perspective and other transformation, stereo imaging elements of visual perception. Digital Image-sampling and quantization serial & parallel Image processing. Unit - 2 Number of lectures

= 8 Title of the unit:Transformations

Image Restoration-Constrained and unconstrained restoration Wiener filter , motion blur remover, geometric and radiometric correction Image data compression-Huffman and other codes transform compression, predictive compression two tone Image compression, block coding, run length coding, and contour coding. Unit - 3 Number of lectures

= 8 Title of the unit:Segmentation Techniques

Segmentation Techniques-thresh holding approaches, region growing, relaxation, line and edge detection approaches, edge linking, supervised and unsupervised classification techniques, remotely sensed image analysis and applications, Shape Analysis – Gestalt principles, shape number, moment Fourier and other shape descriptors, Skelton detection, Hough trans-form, topological and texture analysis, shape matching. Unit - 4 Number of lectures

= 8 Title of the unit: Pattern Recognition

Basics of pattern recognition, Design principles of pattern recognition system, Learning and adaptation, Pattern recognition approaches, Mathematical foundations – Linear algebra, Probability Theory, Expectation, mean and covariance, Normal distribution, multivariate normal densities, Chi squared test. Unit - 5 Number of lectures

= 8 Title of the unit::V: Statistical Patten Recognition

Bayesian Decision Theory, Classifiers, Normal density and discriminant functions, Parameter estimation methods: Maximum-Likelihood estimation, Bayesian Parameter estimation, Dimension reduction methods - Principal

Component Analysis (PCA), Fisher Linear discriminant analysis, Expectation-maximization (EM), Hidden Markov Models (HMM),Gaussian mixture models. 12. Brief Description of self learning / E-learning component. Online video lectures on image processing 13. Books Recommended (3 Text Books + 2-3 Reference Books) xxi) Digital Image Processing - Ganzalez and Wood, Addison Wesley, 1993. xxii) Fundamental of Image Processing - Anil K.Jain, Prentice Hall of India. xxiii) Pattern Classification - R.O. Duda, P.E. Hart and D.G. Stork, Second Edition John Wiley, 2006 xxiv) Digital Picture Processing - Rosenfeld and Kak, vol.I&vol.II, Academic,1982 xxv) Computer Vision - Ballard and Brown, Prentice Hall, 1982 xxvi) An Introduction to Digital Image Processing - Wayne Niblack, Prentice Hall, 1986

SEMESTER VII Cloud Computing

1. Name of the Department CSE 2. Course Name Cloud Computing L T P 3. Course Code 13020706 3 0 0 4. Type of Course (use tick mark) Core () PE(√ ) OE() 5. Pre-requisite (if

any) OS and CN 6. Frequency (use tick


Sem () Every Sem ()

7. Total Number of Lectures, Tutorials, Practical (assuming 14 weeks of one semester) Lectures = 42 Tutorials = 0 Practical = 0 8. Brief Syllabus Unit I: Introduction of delivery models in Cloud Computing Introduction to cloud delivery models, List various cloud delivery models, Advantages of delivery models in cloud, trade-off in cost to install versus flexibility, Cloud service model architecture. Unit II: Infrastructure as a Service (IaaS) Introduction to Infrastructure as a Service delivery model, characteristics of IaaS, Architecture, examples of IaaS, Applicability of IaaS in the industry. Unit III:Platform as a Service (PaaS Introduction to Platform as a Service delivery model, characteristics of PaaS, patterns, architecture and examples of PaaS, Applicability of PaaS in the industry. UnitIV: Software as a Service (SaaS) Introduction to Software as a Service delivery model, characteristics of SaaS, Architecture, examples of SaaS, Applicability of SaaS in the industry. Unit V:Cloud computing Reference Architecture (CCRA) Introduction to Cloud computing reference architecture (CCRA), benefits of CCRA, Architecture overview, versions and application of CCRA for developing clouds. 9. Learning objectives: The objective of this course is to:

1. learn cloud computing delivery model IaaS 2. learn cloud computing delivery model PaaS 3. learn cloud computing delivery model SaaS.


xii) Understand the concepts of virtualization xiii) Understand Cloud delivery models in details xiv) Understand briefly Cloud Computing Reference Architecture xv) Understand how Cloud Computing Architecture can enable transformation, business development and agility

in an organization 11. Unit wise detailed content Unit-1 Number of lectures

= 10 Title of the unit:Introduction of delivery models in Cloud Computing

Introduction to cloud delivery models, List various cloud delivery models, Advantages of delivery models in cloud, trade-off in cost to install versus flexibility, Cloud service model architecture. Unit - 2 Number of lectures

=8 Title of the unit:Infrastructure as a Service (IaaS)

Introduction to Infrastructure as a Service delivery model, characteristics of IaaS, Architecture, examples of IaaS, Applicability of IaaS in the industry. Unit - 3 Number of lectures

= 8 Title of the unit: Platform as a Service (PaaS)

Introduction to Platform as a Service delivery model, characteristics of PaaS, patterns, architecture and examples of PaaS, Applicability of PaaS in the industry.


Title of the unit: Software as a Service (SaaS)

Introduction to Software as a Service delivery model, characteristics of SaaS, Architecture, examples of SaaS, Applicability of SaaS in the industry. Unit - 5 Number of lectures

= 8 Title of the unit: Cloud computing Reference Architecture (CCRA)

Introduction to Cloud computing reference architecture (CCRA), benefits of CCRA, Architecture overview, versions and application of CCRA for developing clouds. 12. Brief Description of self learning / E-learning component This course provides a hands-on comprehensive study of Cloud concepts and capabilities across the various Cloud service models including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Business Process as a Service (BPaaS). IaaS topics start with a detailed study the evolution of infrastructure migration approaches from VMWare/Xen/ KVM virtualization, to adaptive virtualization, and on-demand resources provisioning. PaaS topics cover a broad range of Cloud vendor platforms including Google App Engine, Microsoft Azure, OpenStack and others as well as a detailed study of related platform services such as storage services that leverage Google Storage, Amazon S3, Amazon Dynamo, or other services meant to provide Cloud resources management and monitoring capabilities. 13. Books Recommended (3 Text Books + 2-3 Reference Books)

1. Cloud Computing Architecture (IBM ICE) 2. Cloud computing for Dummies (November 2009) Judith Hurwitz, Robin Bloor, Marcia Kaufman, Fern Halper 3. IBM Cloud Computing http://www.ibm.com/cloud-computing/us/en/ 4. Cloud Computing: A Hands-on Approach by Arshdeep Bahga 5. Cloud Computing Paperback by Anandamurugan and T.Priyaa

curriculum (scheme of examination) & syllabus · engineering. 2. to make b.tech-computer...

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