Uttarakhand Technical University, Dehradun

New Scheme of Examination as per AICTE Flexible Curricula

Bachelor of Technology (B.Tech.) [Computer Science and Engineering]

W.E.F. Academic Session – 2019-20

III Semester

S.No.

Subject

Code

C

ate

go

ry

Subject Name

Maximum Marks Allotted

Total

Marks

Contact Hours per week

Total

Credits

Theory Practical

End

Sem.

Mid

Sem.

Quiz/

Assignment End

Sem.

Labwork

&

Sessional

L

T

P

1. EBEST 01 HSMC-3

Energy &

Environmental

Engineering

70 20 10 - - 100 3 1 - 4

2. BCST-302 DC-1 Discrete Structure 70 20 10 - - 100 3 1 - 4

3.

BCST-303

DC-2 Data

Structure

70

20

10

30

20

150

3

-

2

4

4. BCST-304 DC-3 Digital Systems

70 20 10 30 20 150 3 - 2 4

5. BCST-305 DC-4 Object Oriented

Programming &

Methodology

70 20 10 30 20 150 3 - 2 4

6. BCSP-306 DLC-3 Computer Workshop

(Java Programming ) - - - 30 20 50 - - 4 2

7.

BASP 107

DLC-1

Evaluation of

Internship-I completed

at I year level

- - - - - 50 4 2

8.

BASP 307

DLC-1

90 hrs Internship based

on using various

software’s- internship -

II

To be completed anytime during Third/fourth semester. Its evaluation/credit to be added in fifth semester.

Total 350 100 50 120 130 750 15 2 14 24

NSS/NCC

Uttarakhand Technical University, Dehradun Scheme of Examination as per AICTE Flexible Curricula

W.E.F. Academic Session 2019-20

Bachelor of Technology (B. Tech.) [Computer Science & Engineering]

IV Semester

S.

No

Subject

Code

Ca

teg

ory

Subject Name

Maximum Marks Allotted

Total

Marks

Contact Hours

per week

To

tal

Cre

dit

s

Theory Practical

End

Sem.

Mid Sem.

Exam.

Quiz/

Assignment

End

Sem.

Term work

L

T

P Lab Work &

Sessional

1. BAST 401 BSC Mathematics- III

70 20 10 - - 100 3 1 - 4

2. BCST 402 DC Analysis Design of Algorithm 70 20 10 30 20 150 2 1 2 4

3. BCST 403 DC Software Engineering 70 20 10 30 20 150 3 1 2 5

4. BCST 404 DC Computer Org. & Architecture 70 20 10 30 20 150 3 1 2 5

5. BCST 405 DC Operating Systems 70 20 10 30 20 150 3 0 2 4

6. BCSP 406 DLC* Programming Practices - - - 30 20 50 - - 4 2

7. BCSP 407 DLC 90 hrs Internship based on using various software’s –Internship -II To be completed anytime during fourth semester. Its evaluation/credit to be added in fifth semester. 3

Total 350 100 50 150 100 750 14 4 12 24

8. BCST 408 MC Cyber Security Non-credit course

NSS/NCC

*A minimum of 2hours per week should be allotted for the Virtual Lab along with the slot fixed for the conventional lab classes. MST: Minimum of two mid semester tests to be conducted.

1 Hr Lecture 1 Hr Tutorial 2 Hr Practical

1 Credit 1 Credit 1 Credit

Uttarakhand Technical University, Dehradun

New Scheme of Examination as per AICTE Flexible Curricula Bachelor of

Technology (B. Tech.)

W.E.F. Academic Session -2019-20

Branch- Computer Science and Engineering (Sem: III)

DETAILED SYLLABUS

COURSE OBJECTIVES:

The Course will create awareness among students about Non-Conventional

sources of energy technologies and provide adequate inputs on a variety of

issues.

More precisely, the objectives are:

Conventional and non- conventional energies and its environmental impacts

Environmental changes

Environmental pollution and Types

Environmental impact assessment

Study of natural resources and ecosystems

Industrial system and its environmental impacts

Course Contents:

Module 1: Energy technologies and environment: Electrical energy and steam energy; Fossil

fuels, hydropower and nuclear energy; Solar energy, wind energy and biofuels; Wave, ocean

thermal, tidalenergy and ocean currents; Geothermal energy; Future energy sources; Hydrogen

fuels; Sustainable energy

Module 2:Environment pollution, global warming and climate change: Air pollution (local,

regional and global); Water pollution problems; Land pollution and food chain contaminations;

Carbon cycle, greenhouse gases and global warming; Climate change – causes and consequences;

Carbon footprint; Management of greenhouse gases at the source and at the sinks

Module 3: Ecology, Structure and functioning of natural ecosystems: Ecology, ecosystems

and their structure, functioning and dynamics; Energy flow in ecosystems; Biogeochemical cycles

and climate; Population and communities

EBEST 01

Energy & Environmental

Engineering 3L:1T: 0P 4 credits

Module 4: Natural resources: Human settlements and resource consumption; Biological, mineral

and energy resources; Land, water and air; Natural resources vis-à-vis human resources and

technological resources; Concept of sustainability; Sustainable use of natural resources

Module 5: Agricultural, industrial systems and environment: Agricultural and industrial

systems visà-vis natural ecosystems; Agricultural systems, and environment and natural resources;

Industrial systems and environment

Textbooks/References:

1. Bharucha, E., Textbook of Environmental Studies, Universities Press (2005).

2. Chapman, J.L. and Reiss, M.J., Ecology-Principles and Application, Cambridge

University Press (LPE) (1999).

3. Joseph, B., Environmental Studies, Tata McGraw-Hill (2006).

4. Eastop, T.P. and Croft, D.R. Energy Efficiency for Engineers and Technologists,

Longman and Harow (2006).

5. Miller, G.T., Environmental Science- Working with Earth, Thomson (2006).

6. Wright, R.T., Environmental Science-Towards a sustainable Future, Prentice Hall

(2008) 9thed.

Course Objectives:

Throughout the course, students will be expected to demonstrate their understanding of

Discrete Mathematics by being able to do each of the following:

1. Use mathematically correct terminology and notation.

2. Construct correct direct and indirect proofs.

3. Use division into cases in a proof.

4. Use counterexamples.

5. Apply logical reasoning to solve a variety of problems.

Course Outcomes:

1. For a given logic sentence express it in terms of predicates, quantifiers, and logical

connectives

2. For a given a problem, derive the solution using deductive logic and prove the solution

based on logical inference

3. For a given a mathematical problem, classify its algebraicstructure

4. Evaluate Boolean functions and simplify expressions using the properties of Boolean

algebra

5. Develop the given problem as graph networks and solve with techniques of graphtheory.

Module 1:Sets, relations and functions: (8 hours)

Basic operations on sets, Cartesian products, disjoint union (sum), and power sets.

Different types of relations, their compositions and inverses. Different types of

functions, their compositions and inverses.

Module 2:Propositional Logic: (6 hours)

Syntax and semantics, proof systems, satisfiability, validity, soundness,

completeness, deduction theorem, etc. Decision problems of propositional logic.

Introduction to first order logic and first order theory.

Module 3:Partially ordered sets: (6 hours)

Complete partial ordering, chain, lattice, complete, distributive, modular and

complemented lattices. Boolean and pseudo Boolean lattices.

Module 4:Algebraic Structures: (6 hours)

Algebraic structures with one binary operation – semigroup, monoid and group.

BCST 302 Discrete Structure 3L:1T: 0P 4 credits

Cosets, Lagrange’s theorem, normal subgroup, homomorphic subgroup. Congruence

relation and quotient structures. Error correcting code. Algebraic structures with two

binary operations- ring, integral domain, and field. Boolean algebra and boolean ring

(Definitions and simple examples only).

Module 5:Introduction to Counting:(6 hours)

Basic counting techniques – inclusion and exclusion, pigeon-hole principle, permutation, combination, summations. Introduction to recurrence relation and

generating functions.

Module 6:Introduction to Graphs: (8 hours)

Graphs and their basic properties – degree, path, cycle, subgraph, isomorphism, Eulerian and Hamiltonian walk,trees.

Textbooks/References:

1. C. L. Liu, Elements of Discrete Mathematics, 2nd Ed., Tata McGraw-Hill,2000. 2. R. C. Penner, Discrete Mathematics: Proof Techniques and Mathematical

Structures, World Scientific,1999.

3. R. L. Graham, D. E. Knuth, and O. Patashnik, Concrete Mathematics,

2nd Ed., Addison-Wesley,1994.

4. K. H. Rosen, Discrete Mathematics and its Applications, 6th Ed., Tata

McGraw-Hill, 2007.

5. J. L. Hein, Discrete Structures, Logic, and Computability, 3rd Ed., Jones and

Bartlett, 2010.

6. N. Deo, Graph Theory, Prentice Hall of India,1974. 7. S. Lipschutz and M. L. Lipson, Schaum's Outline of Theory and Problems of

Discrete Mathematics, 2nd Ed., Tata McGraw-Hill,1999. 8. J. P. Tremblay and R. P. Manohar, Discrete Mathematics with

Applications to Computer Science, Tata McGraw-Hill,1997.

BCST 303 Data Structure 3L:0T: 2P 4 credits

Course Objectives:

1. Understand and remember algorithms and its analysis procedure.

2. Introduce the concept of data structures through ADT including List, Stack, Queues.

3. To design and implement various data structure algorithms.

4. To introduce various techniques for representation of the data in the real world.

5. To develop application using data structure algorithms.

6. Compute the complexity of various algorithms.

Course Outcomes:

1. Select appropriate data structures as applied to specified problem definition.

2. Implement operations like searching, insertion, and deletion, traversing mechanism etc.on

various data structures.

3. Students will be able to implement Linear and Non-Linear data structures.

4. Implement appropriate sorting/searching technique for given problem.

5. Design advance data structure using Non-Linear data structure.

6. Determine and analyze the complexity of given Algorithms.

Module 1:

Introduction:

Basic Terminologies: Elementary Data Organizations, Data Structure, Operations: insertion, deletion, traversal etc.; Analysis of an Algorithm, AsymptoticNotations, Time-Space trade off.

Searching: Linear Search and Binary Search Techniques and their complexity analysis.

Module 2:

Stacks and Queues: ADT Stack and its operations: Algorithms and their complexityanalysis,

Applications of Stacks: Expression Conversion and evaluation-correspondingalgorithms and

complexity analysis. ADT queue, Types of Queue: Simple Queue, CircularQueue, Priority Queue;

Operations on each types of Queues: Algorithms and their analysis.

Module 3:

Linked Lists:Singly linked lists: Representation in memory, Algorithms of severaloperations:

Traversing, Searching, Insertion into, Deletion from linked list; Linkedrepresentation of Stack and

Queue, Header nodes, Doubly linked list: operations on it andalgorithmic analysis; Circular

Linked Lists: all operations their algorithms and the complexity analysis.

Trees: Basic Tree Terminologies, Different types of Trees: Binary Tree, Threaded BinaryTree,

Binary Search Tree, AVL Tree; Tree operations on each of the trees and their algorithms with

complexity analysis. Applications of Binary Trees. B Tree, B+ Tree: definitions, algorithms and

analysis.

Module 4:

Sorting and Hashing: Objective and properties of different sorting algorithms:Selection Sort, Bubble Sort, Insertion Sort, Quick Sort, Merge Sort, Heap Sort; Performance and Comparison among all the methods, Hashing.

Graph: Basic Terminologies and Representations, Graph search and traversal algorithms

andcomplexity analysis.

Suggested books:

1. “Fundamentals of Data Structures”, Illustrated Edition by Ellis Horowitz, Sartaj Sahni, Computer Science Press.

Suggested reference books:

1.Algorithms, Data Structures, and Problem Solving with C++”, Illustrated Edition by Mark Allen Weiss, Addison-Wesley Publishing Company

2. “How to Solve it by Computer”, 2nd Impression by R. G. Dromey, Pearson Education

BCST 304 Digital Systems 3L:0T: 2P 4 credits

COURSE OBJECTIVES:

The objectives of this course are to:

1. Introduce the concept of digital and binary systems

2. Be able to design and analyze combinational logic circuits.

3. Be able to design and analyze sequential logic circuits.

4. Understand the basic software tools for the design and implementation of digital circuits

and systems.

5. Reinforce theory and techniques taught in the classroom through experiments and

projects in the laboratory.

Course Contents:

Module 1: Number Systems Binary Codes (10 hours): Number System and its arithmetic,

conversion between bases, Boolean algebra, Canonical form, SOP & POS forms, Minimization of

Boolean Functions: K Map (upto 5 variables), Quine-Mcclusky method, Error detection &

correcting codes, Hamming codes, Binary codes.

Module 2: Combinational Logic Circuits: (8 hours): Introduction to Combinational Circuits,

Analysis and Design Procedure , Binary Adder, Subtractor, Parallel Adder/Subtractor, Carry Look

Ahead Adder, Decoder, Encoder, Priority Encoder, Digital Multiplexer, Magnitude Comparator.

Module 3: Sequential Circuits Fundamentals (10 hours): Basic Architectural Distinctions

between Combinational and Sequential circuits, Flip Flops: SR, JK, D and T Type, Timing and

Triggering Consideration, JK Master Slave, Excitation Table of all Flip Flops, Conversion from

one type of Flip-Flop to another.

Counters: Asynchronous and Synchronous Counters, Design of Up Counters, Design of Down

Counters, Mod Counter, Lock-Out table, Self-Starting Counter.

Module 4: Logic Families: Classification of Logic Families, Parameters: Propagation Delay,

Power Dissipation, Fan-in, Fan-out, Noise Margin. TTL Family, TTL output configurations, ECL

Family, IIL Family, MOS Family. Logic gate design using TTL and MOS.

Module 5: Hazard, Fault Detection & Memories:

Hazard and Fault Detection, Static Hazards, Dynamic Hazards, Determination of Hazards in

Combinational Circuits. Fault Detection Using Fault Table and Path Sensitizing Methods.

Memories: Sequential Access Memories, Random Access Memories, RAM, ROM, PROM,

EPROM, EEPROM, Static and Dynamic RAM cells using nMOS CMOS, Memory Size

Expansion.

Textbooks/References:

1. Digital Systems: Principles and Design, Raj Kamal, Pearson.

2. M. Morris Mano and M. D. Ciletti, Digital Design, M. Morris Mano and M. D. Ciletti, 4th

Edition, pearson.

3. Fundamentals of Digital Circuits A. Anand Kumar PHI 3rd Edition, 2014.

BCST 305 Object Oriented Programming & Methodology 3L:0T: 2P 4 credits

Objectives of the course:

The course will introduce standard tools and techniques for softwaredevelopment, using object

oriented approach, use of a version control system, an automated build process, an appropriate

framework for automated unit and integration tests.

Course Outcomes:

After taking the course, students will be able to:

1. Specify simple abstract data types and design implementations, using abstraction functions to

document them.

2. Recognise features of object-oriented design such as encapsulation, polymorphism, inheritance,

and composition of systems based on object identity.

3. Name and apply some common object-oriented design patterns and give examples of their use.

4. Design applications with an event-driven graphical user interface.

Course contents:

Unit I (8L)

Object Modeling: Objects and classes, links and association, generalization and

inheritance,aggregation, abstract class, multiple inheritance, meta data,candidate keys,

constraints.DynamicModeling: Events and states, operations, nested state diagrams and

concurrency, advanceddynamic modeling concepts, a sample dynamic model.

Unit II (8L)

Functional Modeling: Data flow diagram, specifying operations, constraints, a samplefunctional

model.OMT (object modeling techniques) methodologies, examples and case studiesto

demonstrate methodologies, comparisons of methodologies, SA/SD, JSD.

Unit III (8L)

Java Programming: Introduction, Operator, Data types, Variables, Methods &

Classes,Multithread Programming, I/O, Java Applet.

Unit IV (8L)

Java Library: String Handling, Input/Output exploring Java.io, Networking, ExceptionHandling,

Event Handling, Introduction to AWT, Working with window, Graphics, AWTControls, Layout

Manager and Menus, Images.

Unit V (8L)

Software Development using Java:

Java Swing, Migrating from C++ to java, Application of java, JDBC.

Text Books:

1. Herbert Schieldt, “The Complete Reference: Java”, TMH, 7th Edition.

2. E. Balagurusamy, “Programming in JAVA”, TMH, 4th Edition.

3.James Rumbaugh etal, “Object Oriented Modeling and Design”, PHI

4. Barbara Liskov, Program Development in Java, Addison-Wesley, 2001

References:

1. Bjarne Stroustrup, “C++ Programming Language”, Addison Wesley, 3rd Edition.

2. E. Balagurusamy, “Object Oriented Programming with C++”, TMH, 2008.

BCSP-306 Computer Workshop(Java Programming) 0L:0T:4P 2 credit

1. To write a python program to print HELLO INDIA.

2. To write a java program that takes in command line arguments as input and print

the number of arguments.

3. To write a java program find the division of student.

4. To write a program implements the concept of inheritance.

5. To write a java program method overloading.

6. To write a java program for method over riding.

7. To write a java program exception handling.

8. To write a java program to run applet for drawing various shapes.

9. To write a java program to design a login using JFrame.

10. To write a java program to validate the logging details of user using JDBC concept.

11. To write a python program Insertionsort.

12. To write a python program mergesort.

13. To write a python program first n primenumbers.

14. To write a python program simulate bouncing ball in Pygame.

Uttarakhand Technical University, Dehradun

New Scheme of Examination as per AICTE Flexible Curricula Bachelor of

Technology (B. Tech.)

W.E.F. Academic Session -2019-20

Branch- Computer Science and Engineering (Sem: IV)

DETAILED SYLLABUS

BAST 401 Mathematics-III 3L:1T:0P 4 credits

Course Objective: The objective of this course is to familiarize the students with Laplace Transform,

Fourier Transform, techniques in numerical methods & some statistical techniques. It

aims to present the students with standard concepts and tools at B.Tech first year to

superior level that will provide them well towards undertaking a variety of problems in

the concern discipline.

The students will learn:

The idea of Laplace transform of functions and their applications.

The idea of Fourier transform of functions and their applications.

To evaluate roots of algebraic and transcendental equations.

Interpolation, differentiation, integration and the solution of differential

equations.

The basic ideas of statistics including measures of central tendency, correlation,

regression and their properties.

Module 1: Laplace Transform: (10 hours)

Definition of Laplace transform, Existence theorem, Laplace transforms of derivatives and

integrals, Initial and final value theorems, Unit step function, Dirac- delta function, Laplace

transform of periodic function, Inverse Laplace transform, Convolution theorem, Application to

solve linear differential equations.

Module 2: Fourier Transforms: (9 hours)

Fourier integral, Fourier Transform , Complex Fourier transform, Inverse Transforms,

Convolution Theorem , Fourier sine and cosine transform, Applications of Fourier transform to

simple one dimensional heat transfer equations.

Module 3: Solution of Algebraic and Transcendental equations & Interpolation (8 hours)

Number and their accuracy ,Solution of algebraic and transcendental equations: Bisection

method, Iteration method , Newton-Raphson method and Regula-Falsi method. Rate of

convergence of these methods (without proof),

Interpolation : Finite differences, Relation between operators, Interpolation using Newton’s

forward and backward difference formula .Interpolation with unequal intervals: Newton’s

divided difference and Lagrange’s formula.

Module 4: Numerical differentiation, Integration & Solution of ODE (10 hours)

Numerical Differentiation, Numerical integration: Trapezoidal rule, Simpson’s 1/3rd and 3/8

rule

Runge- Kutta method of fourth order for solving first order linear differential equations.

Milne’s predicator-corrector method.

Module 5: Statistical Techniques (10 hours)

Introduction: Measures of central tendency, Moments, Moment generating function (MGF) ,

Skewness, Kurtosis, Curve Fitting : Method of least squares, Fitting of straight lines, Fitting of

second degree parabola, Exponential curves. Correlation and Rank correlation, Regression

Analysis: Regression lines of y on x and x on y, regression coefficients, properties of

regressions coefficients and non-linear regression.

Reference Books:

1. E. Kreyszig: Advanced Engineering Mathematics; John Wiley & Sons

2. B.V. Ramana: Higher Engineering Mathematics; Tata McGraw- Hill Publishing

Company Limited, New Delhi.

3. Peter V.O’ Neil. Advanced Engineering Mathematics, Thomas ( Cengage) Learning

4. B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers, 35th Edition,

2000.

5. T.Veerarajan : Engineering Mathematics (for semester III), Tata McGraw-Hill, New

Delhi.

6. R.K. Jain and S.R.K. Iyenger: Advance Engineering Mathematics; Narosa Publishing

House, New Delhi.

7. P. Kandasamy, K. Thilagavathy, K. Gunavathi, Numerical Methods, S. Chand &

Company, 2nd Edition, Reprint 2012.

8. S.S. Sastry, Introductory methods of numerical analysis, PHI, 4th Edition, 2005.

9. N.P. Bali and Manish Goyal, Computer Based Numerical and Statistical Techniques ,

Laxmi Publications, Reprint, 2010.

10. J.N. Kapur: Mathematical Statistics; S. Chand & Sons Company Limited, New Delhi.

11. D.N.Elhance,V. Elhance & B.M. Aggarwal: Fundamentals of Statistics; Kitab Mahal

Distributers, New Delhi.

COURSE OUTCOMES( COs):

At the end of this course, the students will be able to:

Remember the concept of Laplace transform and apply in solving real life problems.

Understand the concept of Fourier transform to evaluate engineering problems

Understand to evaluate roots of algebraic and transcendental equations.

Understand interpolation, differentiation, integration and the solution of differential

equations.

Understand the concept of correlation, regression, moments, skewness and kurtosis and curve

fitting.

BCST 402 Analysis Design of Algorithms 2L:1T:2P 4 Credits

Objectives of the course

Analyze the asymptotic performance of algorithms.

Write rigorous correctness proofs for algorithms.

Demonstrate a familiarity with major algorithms and data structures.

Apply important algorithmic design paradigms and methods of analysis.

Synthesize efficient algorithms in common engineering design situations.

Detailed contents:

Module 1:

Introduction: Characteristics of algorithm. Analysis of algorithm: Asymptotic analysis of complexity

bounds – best, average and worst-case behavior; Performance measurements of Algorithm, Time and

space trade-offs, Analysis of recursive algorithms through recurrence relations: Substitution

method, Recursion tree method and Masters’ theorem.

Module 2:

Fundamental Algorithmic Strategies: Brute-Force, Greedy,Dynamic Programming, Branch- and- Bound

and Backtracking methodologies for the design of algorithms; Illustrations of these techniques

for Problem-Solving , Bin Packing, Knap Sack TSP. Heuristics – characteristics and their

applicationdomains.

Module 3:

Graph and Tree Algorithms: Traversal algorithms: Depth First Search (DFS) and Breadth First

Search (BFS); Shortest path algorithms, Transitive closure, Minimum Spanning Tree, Topological

sorting, Network Flow Algorithm.

Module 4:

Tractable and Intractable Problems: Computability of Algorithms, Computability classes – P, NP, NP-

complete and NP-hard. Cook’s theorem, Standard NP-complete problems and Reduction techniques.

Module 5:

Advanced Topics: Approximation algorithms, Randomized algorithms, Class of problems beyond NP –

P SPACE

Suggested books:

1. Introduction to Algorithms, 4TH Edition, Thomas H Cormen, Charles E Lieserson, Ronald L

Rivest and Clifford Stein, MIT Press/McGraw-Hill.

2. Fundamentals of Algorithms – E. Horowitz et al.

Suggested reference books

1. Algorithm Design, 1ST Edition, Jon Kleinberg and ÉvaTardos, Pearson.

2. Algorithm Design: Foundations, Analysis, and Internet Examples, Second Edition, Michael T

Goodrich and Roberto Tamassia, Wiley.

3. Algorithms -- A Creative Approach, 3RD Edition, UdiManber, Addison-Wesley,

Reading, MA.

Course Outcomes

1. For a given algorithms analyze worst-case running times of algorithms based on asymptotic

analysis and justify the correctness of algorithms .

2. Describe the greedy paradigm and explain when an algorithmic design situation calls for it. For a

given problem develop the greedy algorithms.

3. Describe the divide-and-conquer paradigm and explain when an algorithmic design situation calls

for it. Synthesize divide-and-conquer algorithms. Derive and solve recurrence relation.

4. Describe the dynamic-programming paradigm and explain when an algorithmic design

situation calls for it. For a given problems of dynamic-programming and develop the dynamic

programming algorithms, and analyze it to determine its computational complexity.

5. For a given model engineering problem model it using graph and write the corresponding algorithm

to solve the problems.

6. Explain the ways to analyze randomized algorithms (expected running time,

probability of error).

7. Explain what an approximation algorithm is. Compute the approximation factor of an

approximation algorithm (PTAS and FPTAS).

BCST 403 Software Engineering 3L:1T:2P 5 credits

Course Objectives:

1. To enable the students to apply a systematic application of scientific knowledge in creating and

building cost effective software solutions to business and other types of problems.

2. To make the students understand project management concepts & their metrics.

3. To make the students understand requirement engineering and its models (Information,

functional, behavioral).

4. Making the students understand to develop quality software, its maintenance & introduce about

software reliability.

Detailed Syllabus:

MODULE-1: INTRODUCTION

Evolving role of software, Software Characteristics, Software crisis, Silver bullet, Software myths,

Software process, Personal Software Process (PSP), Team Software Process (TSP), emergence of

software engineering, Software process, project and product, Software Process Models: Waterfall

Model, Prototype Model, Spiral, Model ,RAD Model, Iterative Model, Incremental Model, Aspect-

oriented Model, Agile Model.

MODULE-2: SOFTWARE PROJECT MANAGEMENT

Project management concepts, Planning the software project, Estimation—LOC based, FP based, Use-

case based, empirical estimation COCOMO- A Heuristic estimation techniques, staffing level

estimation, team structures, staffing, risk analysis and management.

MODULE-3: REQUIREMENTS, ANALYSIS AND SPECIFICATION

Software Requirements engineering, Requirement engineering process, Requirement Engineering

Tasks, Types of requirements, SRS. System modeling: Data Modeling, Functional modeling and

information flow: Data flow diagrams, Behavioral Modeling, The mechanics of structured analysis:

Creating entity/ relationship diagram, data flow model, control flow model, the data dictionary.

MODULE-4: SYSTEM DESIGN

Design principles, the design process; Design concepts: Abstraction, refinement, modularity, software

architecture, control hierarchy, structural partitioning, data structure, software procedure, information

hiding; Effective modular design: Functional independence, Cohesion, Coupling;

MODULE-5: SOFTWARE TESTING AND MAINTENANCE

Testing terminology- error, bug/defect/fault, failure, Verification and validation, Test case design, Static

testing ,Dynamic testing--- Black box testing—Boundary value analysis, White box testing-- basis path

testing, Unit testing, Integration testing, Acceptance Testing

MODULE-6: SOFTWARE QUALITY MODELS AND STANDARDS

Quality concepts, Software quality assurance, SQA activities, Formal approaches to SQA; Statistical

software quality assurance; CMM, The ISO 9126 Standard

Course Outcomes:

The student will be able to

1. Implement Software life cycle models and have a knowledge of different phases of Software

life cycle

2. Identify, formulate, review, estimate and schedule complex software projects using principles of

mathematics.

3. Create a bug free software with good design and quality by using appropriate techniques and

modern engineering and IT tools.

4. Analyze verification, validation activities, static, dynamic testing, debugging tools and techniques

and importance of working in teams.

REFERENCES:

1. Software Engineering – A Practitioner’s Approach, Roger S. Pressman, 1996, MGH.

2. Fundamentals of software Engineering,Rajib Mall, PHI

3. Software Engineering by Ian sommerville, Pearson Edu, 5th edition, 1999, AW,

4. Software Engineering – David Gustafson, 2002, T.M.H

5. Software Engineering Fundamentals Oxford University, Ali Behforooz and Frederick J.

Hudson 1995,JW&S,

6. An Integrated Approach to software engineering by Pankaj jalote , 1991 Narosa

BCST 404 Computer Organization & Architecture 3L:1T:2P 5 credits

Objectives of the course:

To expose the students to the following :

1. How Computer Systems work & the basic principles

2. Instruction Level Architecture and Instruction Execution

3. The current state of art in memory system design

4. How I/O devices are accessed and its principles.

5. To provide the knowledge on Instruction Level Parallelism

6. To impart the knowledge on micro programming

7. Concepts of advanced pipelining techniques.

Detailed contents:

Module 1

Functional blocks of a computer: CPU, memory, input-output subsystems, control unit.

Instruction set architecture of a CPU – registers, instruction execution cycle, RTL

interpretation of instructions, addressing modes, instruction set. Case study – instruction sets of

some common CPUs.

Data representation: signed number representation, fixed and floating point representations,

character representation. Computer arithmetic – integer addition and subtraction, ripple carry adder,

carry look-ahead adder, etc. multiplication – shift-andadd, Booth multiplier, carry save multiplier, etc.

Division restoring and non-restoring techniques, floating point arithmetic.

Module 2:

Introduction to x86 architecture.

CPU control unit design: hardwired and micro-programmed design approaches, Case study – design of

a simple hypotheticalCPU.

Memory system design: semiconductor memory technologies, memory organization.

Peripheral devices and their characteristics: Input-output subsystems, I/O device interface,

I/O transfers – program controlled, interrupt driven and DMA, privileged and non-privileged

instructions, software interrupts and exceptions. Programs and processes – role of interrupts in

process state transitions, I/O device interfaces – SCII, USB

Module 3:

Pipelining: Basic concepts of pipelining, throughput and speedup, pipeline hazards.

Parallel Processors: Introduction to parallel processors, Concurrent access to memory and

cache coherency.

Module 4:

Memory organization: Memory interleaving, concept of hierarchical memory organization, cache

memory, cache size vs. block size, mapping functions, replacement algorithms, write policies.

Suggested books:

1. “Computer Organization and Design: The Hardware/Software Interface” , 5th Edition by

David A. Patterson and John L. Hennessy, Elsevier.

2. “ Computer Organization and Embedded Systems” , 6th Edition by CarlHamacher,

McGraw Hill Higher Education.

Suggested reference books:

1. “ Computer Architecture and Organization”, 3rd Edition by John P. Hayes,

WCB/McGraw-Hill

2. “ Computer Organization and Architecture: Designing for Performance” , 10th Edition by

William Stallings, Pearson Education.

3. “ Computer System Design and Architecture”, 2nd Edition by Vincent P. Heuring and Harry

F. Jordan, Pearson Education.

Course outcomes

1. Draw the functional block diagram of a single bus architecture of a computer and describe the

function of the instruction execution cycle, RTL interpretation of instructions, addressing modes,

instruction set.

2. Write assembly language program for specified microprocessor for computing 16 bit

multiplication, division and I/O device interface (ADC, Control circuit, serial

port communication).

3. Write a flowchart for Concurrent access to memory and cache coherency in Parallel Processors

and describe the process.

4. Given a CPU organization and instruction, design a memory module and analyze its operation by

interfacing with the CPU.

5. Given a CPU organization, assess its performance, and apply design techniques to enhance

performance using pipelining, parallelism and RISC methodology

BCST 405 Operating Systems 3L:0T:2P 4 credits

Objectives of the course

To learn the fundamentals of Operating Systems.

1. To learn the mechanisms of OS to handle processes and threads and their communication

2. To learn the mechanisms involved in memory management in contemporary OS

3. To gain knowledge on distributed operating system concepts that includes architecture, Mutual

exclusion algorithms, deadlock detection algorithms and agreement protocols

4. To know the components and management aspects of concurrency management

Detailed contents

Module 1:

Introduction: Concept of Operating Systems, Generations of Operating systems, Types of

Operating Systems, OS Services, System Calls, Structure of an OS - Layered, Monolithic,

Microkernel Operating Systems, Concept of Virtual Machine. Case study on UNIX and WINDOWS

Operating System.

Module 2:

Processes: Definition, Process Relationship, Different states of a Process, Process State transitions,

Process Control Block (PCB), Context switching

Thread: Definition, Various states, Benefits of threads, Types of threads, Concept of multithreads,

Process Scheduling: Foundation and Scheduling objectives, Types of Schedulers, Scheduling criteria:

CPU utilization, Throughput, Turnaround Time, Waiting Time, Response Time; Scheduling algorithms:

Pre-emptive and Non pre-emptive, FCFS, SJF, RR; Multiprocessor scheduling: Real Time scheduling:

RM and EDF.

Module 3:

Inter-process Communication: Critical Section, Race Conditions, Mutual Exclusion, Hardware

Solution, Strict Alternation, Peterson’s Solution, The Producer\ Consumer Problem,

Semaphores, Event Counters, Monitors, Message Passing, Classical IPC Problems: Reader’s &

Writer Problem, Dinning Philosopher Problem etc.

Module 4:

Deadlocks: Definition, Necessary and sufficient conditions for Deadlock, Deadlock Prevention,

Deadlock Avoidance: Banker’s algorithm, Deadlock detection and Recovery.

Module 5:

Memory Management: Basic concept, Logical and Physical address map, Memory allocation:

Contiguous Memory allocation – Fixed and variable partition– Internal and External fragmentation and

Compaction; Paging: Principle of operation – Page allocation–Hardware support for paging,

Protection and sharing, Disadvantages of paging.

Virtual Memory: Basics of Virtual Memory – Hardware and control structures – Locality of

reference, Page fault , Working Set , Dirty page/Dirty bit – Demand paging, Page Replacement

algorithms: Optimal, First in First Out (FIFO), Second Chance (SC), Not recently used (NRU) and

Least Recently used (LRU).

Module 6:

I/O Hardware: I/O devices, Device controllers, Direct memory access Principles of I/O Software:

Goals of Interrupt handlers, Device drivers, Device independent I/O software, Secondary-Storage

Structure: Disk structure, Disk scheduling algorithms

File Management: Concept of File, Access methods, File types, File operation, Directory structure, File

System structure, Allocation methods (contiguous, linked, indexed), Free- space management (bit

vector, linked list, grouping), directory implementation (linear list, hash table), efficiency and

performance.

Disk Management: Disk structure, Disk scheduling - FCFS, SSTF, SCAN, C-SCAN, Disk reliability,

Disk formatting, Boot-block, Bad blocks

Suggested books:

1. Operating System Concepts Essentials, 9th Edition by AviSilberschatz, Peter Galvin, Greg Gagne,

Wiley Asia Student Edition.

2. Operating Systems: Internals and Design Principles, 5th Edition, William Stallings, Prentice Hall

of India.

Suggested reference books:

1. Operating System: A Design-oriented Approach, 1st Edition by Charles Crowley, Irwin Publishing

2. Operating Systems: A Modern Perspective, 2nd Edition by Gary J. Nutt, Addison-Wesley

3. Design of the Unix Operating Systems, 8th Edition by Maurice Bach, Prentice-Hall of India

4. Understanding the Linux Kernel, 3rd Edition, Daniel P. Bovet, Marco Cesati, O'Reilly and

Associates

Course Outcomes

1. Create processes and threads.

2. Develop algorithms for process scheduling for a given specification of CPU utilization,

Throughput, Turnaround Time, Waiting Time, Response Time.

3. For a given specification of memory organization develop the techniques for optimally

allocating memory to processes by increasing memory utilization and for improving the access

time.

4. Design and implement file management system.

5. For a given I/O devices and OS (specify) develop the I/O management functions in OS as part of a

uniform device abstraction by performing operations for synchronization between CPU and I/O

controllers.

BCSP 406 Programming Practices (Introduction to MATLAB) 0L:0T:4P 2 credits

Course Objectives:

The course is intended to assist undergraduates in learning the basics of programming in general and

programming MATLAB in particular. Basics of programming in MATLAB will be covered, with the

goal of having students become comfortable enough to continue learning MATLAB and other

programming languages on their own.

MODULE 1: INTRODUCTION

Data types and variables: Introduction to MATLAB, Data Types, Inter-conversion of Data types,

MATLAB Variables, Keywords and Constant, Session Command. MATLAB Operators and Operations:

Operators (Arithmetic, Relational, Logical, Bitwise), Set Operations, Operator Precedence,

Mathematical Functions.

MODULE 2: PROGRAMMING IN MATLAB

Script and Function: Decision Making, Loops, branches, Functions, Working on Script File (Creating,

Saving and Executing), MATLAB I/O, Formatted I/O Method.

MODULE 3: ARRAYS AND GRAPHICS

Matrices and Arrays: Introduction to Matrices, Operations on Arrays/Matrices, Manipulations of

Arrays/Matrices, Expansion of Matrix Size, Reduction of Matrices/Arrays order,

Graphics: Introduction to plot, Basic 2-D Plots( Style options, Labels, Axis control, etc.), specialized 2-

D Plots, drawing multiple plots. Using MATLAB for fractals and chaos and Conway game of life

MODULE 4: FILE HANDLING AND DEBUGGING

File Handling: Introduction to file handling, working on files, accessing of Text File, Saving/ Loading

MATLAB Variables, reading data without opening file, reading and writing Excel.

Debugging: Introduction to debugging, Break points, debugger, stepping, watching variable values,

debugging commands.

Course Outcomes:

At the end of the course, students will be able to

1. Use MATLAB for programming purposes

2. Learn and explore MATLAB further on their own

3. Use this learning experience to learn other programming languages.

REFERENCES:

1. Delores M. Etter, David C. Kuncicky, Holly Moore, “Introduction to MATLAB 7.0”, Pearson,

2013.

2. Rudra Pratap, “Getting Started with MATLAB”, OXFORD University Press, 2010.

3. Agam Kumar Tyagi, “MATLAB and Simulink for Engineers”, University Press, 2012.

WEB REFERENCES

https://ocw.mit.edu/courses/mathematics/18-s997-introduction-to-matlab-programming- fall-

2011/syllabus/

BCST 408 Cyber Security Non- Credit Course

Course Objectives:

1. Understand the basic concept of Network Security, their mathematical models.

2. To impart knowledge of major issues in network and computer system security, focusing mainly

on threats from malicious software and To understand common attacks on computer networks

and methods to detect and remediate such attacks.

3. To study various issues in security of MANETS and study various attacks.

4. To provide the students with the competences required for understanding various issues in

security of Wireless Security Networks and also various attacks against security mechanism and

routing.

UNIT-1:

Introduction What is security?, Need of security, Why is security so hard?, various goals of security,

Difference between Vulnerability, Threats, Attacks and control, Security goals, aspects of security,

security services, security attacks, Types of viruses, worms, Trojans.

UNIT-2:

Cyber Security, Security services, digital signature, entity authentication. Authentication applications:

Kerberose 95, X.509 Authentication service, Public key infrastructure. Electronic mail Security: Preety

Good Privacy (PGP), IP Security: IP security overview, IP security architecture, Authentication header,

Encapsulating security Payload, Combining security associations, Key management.

UNIT-3:

Security Attacks in MANET Security issues in MANET, Attacks in MANET: External Attack, Internal

attack, Black hole attack, warm hole attack, grey hole attack, Byzantine attack, Sleep Deprivation

attack, Flooding attack: RREQ flooding attack, Data flooding Attack.

UNIT-4:

Attack against basic mechanism like routing: Spoofed, altered, replayed routing, Information, Selective

forwarding , Sinkhole attacks , Sybil attacks, Wormholes, HELLO flood attacks

Course Outcomes:

After the completion of this course the student will able to:

1. Understand theory of fundamental cryptography, encryption and decryption algorithms,

2. Build secure systems by use of block ciphers like AES, DES.

3. To be familiar with network security designs using available secure solutions and advanced

security issues and technologies.

4. To develop basic security enhancements in MANETS.

5. To know how authentication is implemented in wireless systems and understand authentication

protocols and processes.

REFERENCES:

1. P. Pfleeger, Shari Lawrence Pfleeger Charles: Security in Computing, PHI.

2. William Stalling, Cryptography and Network Security, 3rd Edition. PHI New Delhi

3. William Stalling, Network Security Essentials, 2nd Edition. PHI New Delhi

4. Bruce Schneier, Niels Ferguson : Practical Cryptography, Wiley Dreamtech India Pvt. Ltd.