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Templates The STL C++ Without Bugs Outlook

9. Generic Programming & Effective C++

June 17, 2010


Introduction to C/C++, Tobias Weinzierl page 1 of 33

http://www5.in.tum.de/wiki/index.php/Dr._rer._nat._Tobias_Weinzierl





Outline

• Generic Programming: Templates

• The Standard Template Library

• (More) Effective C++—SomeExamples

• Outlook








—9.1. Templates —

• Sometimes, it is cumbersome to write a feature for one type, as we know that we’llneed exactly the same feature for another type, too.

• Standard example: Technical classes such as lists.

• Study our linked list example. What, if we need this list for doubles and somestructs, too?








Generalisation of the Linked List With Respect to Its Type





Using Type-generic Classes

t e m p l a t e <c l a s s T>c l as s L i n k e d Li s t {

p u b l i c :v o i d a p p e n d (T);

} ;

. . .L i n k e d L i s t m y I n t e g e r L i s t ;m y I n t e g e r L i s t . append ( 1 0 ) ;

L i n k e d L i s t<double> myDoubleList ;m y Do u bl e Li s t . append ( 0 . 1 ) ;

m yD ou bl e Li s t = m y I n t e g e r L i s t ; / / a r r r rg h

• Templates are classes which require a type to be instantiated.• Then, we can use them as standard classes with the template argument replaced

by the concrete type.

• If two template instantiations have different type, they are two completely differentclasses (similar to cut-n-paste).

Writing Type-generic Classes

t e m p l a t e <c l a s s T>c l as s L i n k e d Li s t {

p u b l i c :v o i d append( co n st T& v a l u e ) ;

} ;

t e m p l a t e <c l a s s T>v o i d L i n k e d L i s t<T>::append( co n st T& value ) {

. . .}

• Templates are defined solely in headers.

• Templates are pain to debug.

• However, it is, basically, only “‘replace all types by T”.

• Usually, you will never have to write templates. But you have to be able to use them.

—9.2. The STL —

t e m p l a t e <c l a s s T>

c l a s s s t d : : v e c t o r {. . .} ;

s t d : : v e c t o r myVector ;

myVector . push back ( 2 3 ) ; myVector . push back ( 24 ) ; myVector . push back ( 2 5) ;myVector . s iz e ( ) ;

m yV ec to r [ 1 ] = 1 7 ;m yV ec to r [ 0 ] = m yV ec to r [ 1 ] + m yV ec to r [ 2 ] ;

• C++ comes along with a huge set of standard data structures.

• These data structures all are templates.

• Consequently, the standard library is called standard template library.

• Among the most frequently used types are std::string, std::list (dynamicdata structures), and std::vector (array which could change; however changingit is expensive).

• See http://www.cppreference.com for a comprehensive overview.

The STL vector Class—Some of Its Operations

# i n c l u d e <v e c t o r>

s t d : : v e c t o r myVector ;

assign assign (multiple) elements of a vectorat or [x] modify/return elements of the vectorclear removes all elements from the vector

empty returns true if the vector has no elementserase removes elements from a vectorinsert inserts elements into the vector (vector grows)pop back removes the last element of a vectorpush back appends an element to the end of the vectorsize returns the number of items in the vector. . . . . .

The vector is an abstraction of an array, as we can select individual elements in thesame way we can select elements from an array—with the [] operator. If we make thevector grow or shrink, C++ basically adopts the underlying data structure. However, thisis not efficient!

The STL list Class—Some of Its Operations

# i n c l u d e < l i s t >

s td : : l i s t myList ;

assign assign (multiple) elements of a listclear removes all elements from the listempty returns true if the list is emptyerase removes elements from a list

insert inserts elements into the listpop back removes the last element of a listpush back appends an element to the end of the listpop front removes the first element of a listpush front sets a new first element for the listremove removes entriesreverse inverts the list

size returns the number of items in the list. . . . . .

The list’s signature is similar to the vector signature (consistency). The list is similar toour implementation of the (double) linked list. Inserting new elements, sorting the list,and inverting the whole sequence is rather cheap. However, accessing individualelements explicitly (random access ) is not what a list is made for.

The STL set Class—Some of Its Operations

# i n c l u d e <se t>

s t d : : se t mySet ;

clear removes all elements from the setcount counts the elements in the listempty returns true if the set is empty

erase removes elements from a setinsert inserts elements into the setsize returns the number of items in the set. . . . . .

Again, the signature is similar to the other containers. The set can store any built-intype/struct/class for which the < operator and the == operator are defined.

The STL map Class—Some of Its Operations

# i n c l u d e <map>

std : : map myMap;

clear removes all elements from the mapcount(key) counts the elements in the mapempty returns true if the map is empty

erase(key) removes elements from a mapfind(key) searches for the key and returns an iterator(reference) to the caller

insert(key,value) inserts mapping (pair of key and value) into the mapsize returns the number of items in the map. . . . . .

A map maps entries of the first template type to the second type. Here, integers aremapped to doubles. However, you can plug-in any class you’d like as long as youprovide an equals operator ==.

Loops over STL Containers


c l a s s s t d : : v e c t o r {. . .

} ;

s t d : : v e c t o r myVector ;. . .f o r ( i n t i = 0; i<m yV ec to r . s i z e ( ) ; i + +) {

/ / Do something w i t h my Vec tor [ i ] . For exampl e

myVector [ i ] ++ ;}

• What is the semantics of this code fragment?

• For an iteration, the realisation (linked list, vector, etc.) does not matter.

• This variant however works for vectors only.• Even with a corresponding list operator, the performance would suffer.

The Iterator Concept


c l a s s s t d : : v e c t o r {. . .

} ;

s t d : : v e c t o r myVector ;. . .s t d : : v e c t o r: : i t e r a t o r p = myV ect or . b eg in ( ) ;w h i l e ( p ! = m yV ec to r . end ( ) ) {

∗p = . . . ; / / myVector [ i ] = . . . ; p ++;

}

• The iterator is a class nested into the vector.

• The iterator is used like a pointer is used.

• The iterator hides how we proceed from one element to another.

• There is some iterator-factory-methods such as begin() and end().



T l t Th STL C With t B O tl k

The Iterator Concept—the While Loop Rewritten


c l a s s s t d : : v e c t o r {. . .

} ;

s t d : : v e c t o r myVector ;. . .f o r (

s t d : : v e c t o r: : i t e r a t o r p = m yV ect or . b e gi n ( ) ; p ! = m yV ec to r . end ( ) ; p++

) {∗p = . . . ; / / myVector [ i ] = . . . ; p ++;

}

• The iterator is a class nested into the vector.

• The iterator is used like a pointer is used.• The iterator hides how we proceed from one element to another.




Templates The STL C Without Bugs Outlook

The Const Iterator Concept


c l a s s s t d : : v e c t o r {. . .

} ;

s t d : : v e c t o r myVector ;. . .f o r (

s t d : : v e c t o r: : c o n s t i t e r a t o r p = myVector . b eg in ( ) ;

p != myVector .e nd ( ) ;p++

) {∗p = . . . ; / / myVector [ i ] = . . . ; p ++;

}

• The iterator is a class nested into the vector.• The iterator is used like a pointer is used.

• The iterator hides how we proceed from one element to another.


• Const iterators are not allowed to modify the traversed data structure.

• Thus, they are significantly faster than a standard iterator.




Iterator Variants

• Iterators hide the realisation of a sequence.

• Each STL container provides iterators, i.e. we can chose a different realisation andour code still works efficiently.

• There’s also

• reverse iterators,• const iterators, and• reverse const iterators.









—9.3. C++ Without Bugs —









Virtual Destructors

cl ass EnemyTarget {

p u b l i c :EnemyTarget ( ) { ++numTargets ; }˜EnemyTarget () { −−numTargets ; }

p r i v a t e :s t a t i c i n t numTargets ;

} ;

/ / i n t h e cpp f i l e

i n t EnemyTarget : : numTargets = 0;

Example from “Effective C++”.








p g

Virtual Destructors

cl ass EnemyTarget {

p u b l i c :EnemyTarget ( ) { ++numTargets ; }˜EnemyTarget () { −−numTargets ; }

p r i v a t e :s t a t i c i n t numTargets ;

} ;

cl ass EnemyTank : pu bl i c EnemyTarget {

p u b l i c :EnemyTank ( ) {}˜ EnemyTank ( ) {}

} ;

. . .

EnemyTarget∗ newTarget = new EnemyTank ( ) ;

d e l e te n ewTarg et ;








References vs. Copies as Result Values

c l as s R a t i on a l {

p r i v a t e :i n t numerato r ;i n t denomin ator ;

p u b l i c :R a t i on a l ( ) ;

co n st R a t i o n a l& m u l t i p l y W i t h ( co n st Re a ti o n a l& a no th erNu mb er ) co n st {R a t i o n a l ∗ r e s u l t = new R a t i o n a l ( . . . ) ;

r e t u r n ∗ r e s u l t ;}

} ;

R a t i o n a l a , b ; / / do something w i t h a and b R at i on al c = a . m u l t ip l y W i th ( b ) ;


• Here, the whole Rational object is copied, and copying is time-consuming.

• Reference make the memory handling easier (than with pointers). However, it’ssometimes still tricky. Here, you’ve created a memory leak.








Return a Copy

c l as s R a t i on a l {

p r i v a t e :i n t numerato r ;i n t denomin ator ;

p u b l i c :R a t i on a l ( ) ;

R a t i on a l m u l t i p l y W i t h ( co n st Re a ti o n a l& a no th erNu mb er ) co n st {R a t i o n a l r e s u l t ( . . . ) ;

r e t u r n r e s u l t ;

/ / or , even b e t t e r : r e t u r n R at i on al ( . . . ) ;

}} ;

R a t i o n a l a , b ; / / do something w i t h a and b R at i on al c = a . m u l t ip l y W i th ( b ) ;









Never Redefine Default Parameters

enum ShapeColour {Red, Green , Blue } ;

cl ass Shape {p u b l i c :

v i r t u a l v o i d d ra w ( S ha pe Co lo ur c o l o u r = R ed ) co n st = 0 ;} ;












c l a s s R ec t an gl e : p u b l i c Shape {p u b l i c :v i r t u a l v o i d d ra w ( S ha pe Co lo ur c o l o u r = Green ) co n st = 0 ;

} ;

Shape∗ p r = new Re cta n gle ;p r −> d raw ( ) ; / / what i s t he c ol o ur ?













c l a s s R ec t an gl e : p u b l i c Shape {p u b l i c :v i r t u a l v o i d d ra w ( S ha pe Co lo ur c o l o u r = Green ) co n st = 0 ;

} ;

Shape∗ p r = new Re cta n gle ;p r −> d raw ( ) ; / / what i s t he c ol o ur ?


• pr has a dynamic type which is different from its static type.

• Default parameters are defined statically.

• Who defined this behaviour—we don’t know!







Combine C and C++

• Combining C and C++ is easy if you can recompile the application with a C++

compiler.• Name mangling: Translate C++ names into symbols.

• C and C++ byte codes are not compatible.

• Thus, write headers for your C libraries with

e x t e r n ”C”

v o i d foo ( i n t a , i n t b ) ;








—9.4. Outlook —

• Exceptions & Error Handling

• Debugging

• Integrated Development Environments

• Architectural Patterns & DesignPatterns

• Performance Analysis

• From the Waterfall Model to AgileMethods








Exceptions and Error Handling

v o i d A : : b ar ( ) {

. . . / / he re , we do a d i v i s i o n by zero o r

throw MyException ; / / i t ’ s a c l as s we ’ v e d e fi n ed b ef o re and / / we mi ght pa ss i t many f l a g s d e s c r i b i n g / / t h e e r r o r

}

v o i d A : : f o o ( ) {t r y {

. . .b ar ( ) ;. . .

}c a t c h ( M yE xc ep ti on& e x c e p t i o n ) {

/ / r o l l ba ck a p p l i c a t i o n t o a v a l i d s t a t e }

}








Debugging

Our bug searching strategy:






Debugging

Our bug searching strategy:

s t d : : c ou t << ” v a l ue o f s om et hi ng ” ;

• Debuggers are programs where you can define breakpoints .

• Debuggers allow you to study the values of all variables then.

• Debuggers support single step execution.

• Debuggers sometimes even allow you to modify variables manually.

9. Generic Programming & Effective C++Introduction to C/C++, Tobias Weinzierl page 28 of 33



Integrated Development Environments







Architectural Patterns & Design Patterns

. . . or what is a three tier architecture?

• Read a nice book.• Study http://martinfowler.com/eaaCatalog/.

• Use other’s software—in particular frameworks and libraries (such as Peano,Dune, deal.ii).







Performance Analysis

The simplest tools is gprof , but there’s tons of such software around.

Each sample counts as 0.01 seconds.% cumulative self self total

time seconds seconds calls ms/call ms/call name

33.34 0.02 0.02 7208 0.00 0.00 open

16.67 0.03 0.01 244 0.04 0.12 offtime

16.67 0.04 0.01 8 1.25 1.25 memccpy

16.67 0.05 0.01 7 1.43 1.43 write

16.67 0.06 0.01 mcount0.00 0.06 0.00 236 0.00 0.00 tzset

0.00 0.06 0.00 192 0.00 0.00 tolower

0.00 0.06 0.00 47 0.00 0.00 strlen

0.00 0.06 0.00 45 0.00 0.00 strchr

0.00 0.06 0.00 1 0.00 50.00 main

0.00 0.06 0.00 1 0.00 0.00 memcpy

0.00 0.06 0.00 1 0.00 10.11 print0.00 0.06 0.00 1 0.00 0.00 profil

0.00 0.06 0.00 1 0.00 50.00 report







From the Waterfall Model to Agile Methods







How to Continue

• Read the “Effective” Books• Read the Design Patterns by the Gang of Four

• Read the book Refactoring from Martin Fowler(if you have to use other’s (old) code)

• Read the book Write Great Code(if you want to understand how and while code performs the way it does)

• Attend one of the LRZ courses(http://www.lrz-muenchen.de/services/compute/courses/)(the HPC courses are free for students from all over Germany)

• GPGPU Programming• Visualisation of Large Data Sets• Compact course: Iterative linear solvers and parallelization

• Parallel Programming of High Performance Systems• . . .







How to Continue

• Read the “Effective” Books• Read the Design Patterns by the Gang of Four

• Read the book Refactoring from Martin Fowler(if you have to use other’s (old) code)

• Read the book Write Great Code(if you want to understand how and while code performs the way it does)

• Attend one of the LRZ courses(http://www.lrz-muenchen.de/services/compute/courses/)(the HPC courses are free for students from all over Germany)

• GPGPU Programming• Visualisation of Large Data Sets• Compact course: Iterative linear solvers and parallelization

• Parallel Programming of High Performance Systems• . . .

• . . . write me an email




09 generic programming and effective

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