83
Course Name: DATA STRUCTURES Course Code: 10B11CI211 Course Credits: 4 (3-1-2) Session: Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin and Hemraj

Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Embed Size (px)

Citation preview

Page 1: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Course Name: DATA STRUCTURESCourse Code: 10B11CI211Course Credits: 4 (3-1-2)Session: Jan – Jun 2013

Data Structures Team:

Course Coordinator: Deepak, Nitin and Hemraj

Page 2: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

WHAT THE COURSE IS ABOUT

• Data structures is concerned with the representation and manipulation of data.

• All programs manipulate data.• So, all programs represent data in some way.• Data manipulation requires an algorithm.• We shall study ways to represent data and

algorithms to manipulate these representations.• The study of data structures is fundamental to

Computer Science & Engineering.

Page 3: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

PREREQUISITE

• C• Enumerated data type, void data type• typedef statement• Control statements• Use of memory by a program• Specification of pointers• Memory management functions• Problems with pointers• Various aspects of user defined functions

Page 4: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

WHAT IS DATA STRUCTURE

“A Conceptual and concrete way to organize data for efficient storage and manipulation”

Page 5: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

WHAT IS DATA STRUCTURE

A data structure is a logical and mathematical model of a particular organization of data.

The choice of particular data structure depends upon following consideration:

1.It must be able to represent the inherent relationship of data in the real world.

2.It must be simple enough so that it can process efficiently as and when necessary

Page 6: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

OVERVIEW OF DATA STRUCTURE

• Basic Terms related to data organization

• Data type

• Meaning of data structure

• Factor that influence the choice of data structure

• Different data structure

• Various operation performed on data structure

Page 7: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

BASIC TERMS RELATED TO DATA ORGANIZATION

• Data:Values or set of values.Eg. Observation of experiment, marks obtained by student.• Data item:A data item refers to a single unit of values.Eg. Roll no. name etc.• Entity:That has certain attribute or properties which may be

assigned values.Eg. Student is an entity

Page 8: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

BASIC TERMS RELATED TO DATA ORGANIZATION

• Entity set:Collection of similar entity.Eg. Student of a class• Record:Collection of related data items.Eg. Rollno, Dob, gender, class of a particular student.• File:Collection of related record.Eg. A file containing records of all students in a class

Page 9: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

BASIC TERMS RELATED TO DATA ORGANIZATION

• Key:

A key is a data item in a record that takes unique values and can be used to distinguish a record from other records.

• Information:

Meaningful data, coveys some meaning and hence can be used for decision making

Page 10: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

DATA TYPE

A data type is a collection of values and a set of operation that act on those values

Classification of data type:

1. Primitive data type

2. Abstract data type

3. Polymorphic data type

Page 11: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

PRIMITIVE DATA TYPE

• That is predefined. It is also known as built in data type.

Eg. C have built in data type int, long int, float, double, char.

Page 12: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

ABSTRACT DATA TYPE

• In computing, an abstract data type (ADT) is a specification of a set of data and the set of operations that can be performed on the data. Such a data type is abstract in the sense that it is independent of various concrete implementations.

• The main contribution of the abstract data type theory is that it – (1) formalizes a definition of type (which was only intuitively

hinted on procedural programming) – (2) on the basis of the information hiding principle and – (3) in a way that such formalization can be explicitly

represented in programming language notations and semantics. This important advance in computer science theory (motivated by software engineering challenges in procedural programming) led to the emergence of languages and methodological principles of object-oriented programming.

Page 13: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

POLYMORPHIC DATA TYPE• Very often in programs, a generic operation must be

performed on data of different types. For example, in our bubble sort algorithm for the payroll records, when elements were found out of order in the id[] array, we needed to swap the integer elements in that array as well as the float elements in the hrs[] and rate[] arrays. If we decided to implement this swapping operation as a function, we would need to write two functions: one to swap integers, and another to swap floating point values; even though the algorithm for swapping is the same in both cases.

• The C language provides a mechanism which allows us to write a single swapping function which can be used on any data type. This mechanism is called a polymorphic data type, i.e. a data type which can be transformed to any distinct data type as required..

Page 14: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

THE STUDY OF DATA STRUCTURE INCLUDE:

• Logical description of data structure

• Implementation of data structure

• Quantative analysis of data structure, this include amount of memory, processing time

Page 15: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

TYPES OF DATA STRUCTURES

1. Linear data structure

2. Non linear data structure

Page 16: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

LINEAR DATA STRUCTURE

A data structure whose elements form a sequence, and every element in the structures has a unique predecessor and unique successor.

Eg. Array, linked list, stack and queues.

Page 17: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

NON LINEAR DATA STRUCTURE

A data structure whose elements do not form a sequence, and there is no predecessor and unique successor.

Eg. Trees, graphs

Page 18: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

ARRAYS

Collection of homogenous data elements.

Arrays can be:

1. One dimensional

2. Two dimensional

3. Multi dimensional

Page 19: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

LINKED LIST

• Linked list – Linear collection of self-referential class objects,

called nodes– Connected by pointer links– Accessed via a pointer to the first node of the list– Subsequent nodes are accessed via the link-pointer

member of the current node– Link pointer in the last node is set to null to mark the

list’s end• Use a linked list instead of an array when

– You have an unpredictable number of data elements– Your list needs to be sorted quickly

Page 20: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

The Linked List data structure

[0] [1] [2]array

A B CArray

linked

A B CLinked list

Linked lists are unbounded(maximum number of items limited only by memory)

node

Page 21: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

LINKED LIST

• Types of linked lists:– Singly linked list

• Begins with a pointer to the first node• Terminates with a null pointer• Only traversed in one direction

– Circular, singly linked• Pointer in the last node points back to the first node

– Doubly linked list• Two “start pointers” – first element and last element• Each node has a forward pointer and a backward pointer• Allows traversals both forwards and backwards

– Circular, doubly linked list• Forward pointer of the last node points to the first node and

backward pointer of the first node points to the last node

Page 22: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

LINKED LISTS (VARIATIONS)

• Basic elements:– Head– Node

• Simplest form: Linear-Singly-linked

headA

data pointer

node

A

Head

B C

Page 23: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

LINKED LISTS (VARIATIONS)

• Circular-linked Lists

– The last node points to the first node of the list

• Strengths– Able to traverse the list starting from any point– Allow quick access to first and last records through

a single pointer

• Weakness– A bit complicated during insertion, needs careful

setting of pointer for empty or one-node list

A

Head

B C

Page 24: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

LINKED LISTS (VARIATIONS)• Doubly-linked Lists

– Each inner node points to BOTH successor and the predecessor

• Strengths– Able to traverse the list in any direction– Can insert or delete a node very quickly given only that

node’s address

• Weakness– Requires extra memory and handling for additional

pointers

A

Head

B C

Page 25: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

LINKED LISTS (VARIATIONS)

• Putting together…Circular-doubly-linked lists!

A

Head

B C

Page 26: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

STACK

• Stack – New nodes can be added and removed only at the top– Similar to a pile of dishes– Last-in, first-out (LIFO) – Bottom of stack indicated by a link member to NULL– Constrained version of a linked list

• push– Adds a new node to the top of the stack

• pop– Removes a node from the top – Stores the popped value – Returns true if pop was successful

Page 27: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

DATA STRUCTURES -- STACKS

• A stack is a list in which insertion and deletion take place at the same end– This end is called top– The other end is called bottom

Page 28: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

QUEUES

• Queue– Similar to a supermarket checkout line– First-in, first-out (FIFO) – Nodes are removed only from the head – Nodes are inserted only at the tail

• Insert and remove operations – Enqueue (insert) and dequeue (remove)

Page 29: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

The Queue Operations

• A queue is like a line of people waiting for a bank teller. The queue has a front and a rear.

$ $

FrontRear

Page 30: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

TREES

• Tree nodes contain two or more links– All other data structures we have discussed

only contain one

• Binary trees– All nodes contain two links

• None, one, or both of which may be NULL

– The root node is the first node in a tree. – Each link in the root node refers to a child– A node with no children is called a leaf node

Page 31: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

TREE TERMINOLOGY

There is a uniquepath from the rootto each node.

Root is a level 0, childis at level(parent) + 1.

Depth/height of a treeis the length of the longest path.

level 0

1

2

3

4

Page 32: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

BINARY TREE• Each node has two successors

– one called the left child– one called the right child– left child and/or right child may be empty

A binary tree is either - empty or - consists of a root and two binary trees, one called the left subtree and one called the right subtree

Page 33: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

GRAPHSG = (V, E)

a vertex may have: 0 or more predecessors 0 or more successors

Page 34: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

abstract containers

hierarchical (1 to many)

graph (many to many)first ith last

sequence/linear (1 to 1)

set

Page 35: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

HEAPS

Heap is a binary tree that satisfy the following property:

• Shape property• Order propertyShape property states that heap is complete or

nearly complete binary tree.Order property states that:1. Either the element at any node is smallest of

all of its children, called min heap2. Element at any node is largest of all of its

children, called max heap.

Page 36: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

HASH TABLES

• There are many application that require a dynamic structure that support only insert, search and delete operations. These operations are commonly known as dictionary operations. A hash table is an effective data structure for implementing dictionaries.

Page 37: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

COMMON OPERATIONS ON DATA STRUCTURE

1. Traversal:-Accessing each element exactly once in order to process it.

2. Searching:-Finding the location of a given element.

3. Insertion:-Adding the new element to the structure.

4. Deletion:-Removing a existing element from the structure.

5. Sorting:-Arranging the elements in logical order.

6. Merging:-Combining the elements of two similar sorted structures into a single structure.

Page 38: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

ENUMERATED DATA TYPE

• Variable of enumerated data type enhance the readability of the program.

enum boolean {false, true};Here boolean is called tag name for the user

defined data type. Then we can declare variable of this type as follows:

enum boolean flag;Then we can assign value false or true to variable

flag, and also we can compare the value of flag with these values.

Page 39: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

void DATA TYPE• This is also known as empty data type, is useful in many situation;1. Void functionname(int x, int y)

{}

Functionname() does not return any value.2. Int functionname(void)

{}

Functionname() does not take any rgument.3. Void main()

{void *ptr;int x=5;ptr=&x;printf(“value pointed to pointer is now %d”,*(int*)ptr);

}Void pointer cannot be directly dereferenced without type casting. This

is because the compiler cannot determie the size of the value the pointer points to.

Page 40: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

REDEFINING DATA TYPES

• Using typedef statement we can make it possible to declare variables of user defined data types as with built in data types by redefining the user defined data type and giving our own name.

typedef enum{false, true} boolean;

The word boolean becomes name of the new defined data type.

boolean flag;

Page 41: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

CONTROL STATEMENTS

1. Decision making statements• if statement• if-else statement• switch statement2. Looping Statements• for statement• while statement• do while statement3. Jumping statements• brake statement• continue statement• goto statement

Page 42: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

MEMORY USE IN C

STACK

HEAP

BSS

CONST

DATA

TEXT

High Memory

Low Memory

Initialized and un initialized local variable

Memory allocated with malloc(). Calloc(), and realloc() functions

Un initialized static variable

Read only variable

Initialized & un initialized global variables & initialized static variables

Program code

Page 43: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

POINTER

• Pointer is a variable which contains reference of another variable

Address of x value of x

px x

Pointerpx=&x

Page 44: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

DECLARATION OF POINTER• “*” is used to declare and dereference the

pointers.data type *ptvar;

int *ip; /*declare ip to be pointer to an integer*/ *ip=5;/* assign 5 to the integer pointer to which ip

points*/

address 5

ip

Page 45: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

POINTER OPERATOR

• Two operators:

&-----address of

*------at address in

X=8 let x be at 100 (x at 100)

Ip=&x ip contains 100 (ip at 200)

a=*ip contains 8 (a at 250)

8

100

8

Page 46: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

ASSIGNMENT IN POINTER

GivenInt x;Double y;Int *a,*b;double *c;

a=&x; /* a now points to x*/b=a; /*b now points to the same variable as a

points */c=&y; /* c points to y */

Page 47: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

POINTER TO A POINTER

• Variable that hold an address of a another variable that in turn holds an address of another variable, this type of variable is know as pointer to pointer.

• Pointer to pointer will be declared as

**ptr;

Page 48: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

DYNAMIC MEMORY MANAGEMENT

Memory management functions

Function name

Description

malloc Allocate memory from heap

calloc Allocate memory from heap and initializes the allocated memory to zeros

realloc Readjusts the existing block and copies the contents to new location

free Deallocates block allocated by malloc, calloc and realloc fuctions

Page 49: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

DYNAMIC MEMORY ALLOCATION

• Dynamic memory allocation– Obtain and release memory during execution

• malloc– Takes number of bytes to allocate

• Use sizeof to determine the size of an object– Returns pointer of type void *

• A void * pointer may be assigned to any pointer• If no memory available, returns NULL

– ExamplenewPtr = malloc( sizeof( struct node ) );

• free– Deallocates memory allocated by malloc– Takes a pointer as an argument– free ( newPtr );

Page 50: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

calloc()

The calloc() function dynamically allocates memory and automatically initializes the memory to zeroes. Example

newPtr = calloc( 5,sizeof( struct node ) );

Page 51: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

realloc()

The realloc() function changes the size of previously dynamically allocated memory with malloc(),calloc() or realloc function() functions.

The prototype of realloc() function is Void *realloc(void *block,size_t size);It takes two arguments, first argumant is

pointer to the original object and second argument is new size of the object.

Page 52: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

free()

The free() function deallocates a memory block previously allocated with malloc(), calloc(), or realloc() functions. Prototype for free function is

void free(void *block);

It takes one argument that specify the pointer to the allocated block.

Page 53: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

DEBUGGING POINTERS

The pointer can be the source of mysterious and catastrophic program bugs. Common bugs related to related to pointer and memory management is

1. Dangling pointer

2. Null pointer assignment

3. Memory leak

4. Allocation failure

Page 54: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

STRUCTURES

A structure is a collection of data elements, called fields which may be of different type.

Individual elements of a structure variable are accessed using dot operator (.), if a pointer is used to point to a structure variable , then arrow operator (->) is used.

Page 55: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

STRUCTURE

Example of complex data structures and the corresponding self referential structure to represent these data structure.

Next pointer field

Information field

head

1200 1201 1202 X

Page 56: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

STRUCTURE

typedef struct nodetype{

int info;

struct nodetype *next;

} node;

node * head;

Page 57: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Recursion

Page 58: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Divide-and-conquer

Page 59: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

What is recursion?

Page 60: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Recursive functions

Page 61: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Nature of recursion

Page 62: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Nature of recursion

Page 63: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Types of Recursion• Direct Recursion• Indirect Recursion

Page 64: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Iteration vs. recursion

Page 65: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Recursion: sum()

Page 66: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Recursion: sum()

Page 67: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

How does recursion work?

Page 68: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

How does recursion work?

Page 69: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

How does recursion work?

Page 70: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

RecursionRecursive functions

– Functions that call themselves

– Can only solve a base case

– Divide a problem up into• What it can do• What it cannot do

– What it cannot do resembles original problem– The function launches a new copy of itself (recursion

step) to solve what it cannot do

– Eventually base case gets solved• Gets plugged in, works its way up and

solves whole problem

Page 71: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

RecursionExample: factorials–5! = 5 * 4 * 3 * 2 * 1

–Notice that•5! = 5 * 4!•4! = 4 * 3! ...

–Can compute factorials recursively

–Solve base case (1! = 0! = 1) then plug in•2! = 2 * 1! = 2 * 1 = 2;•3! = 3 * 2! = 3 * 2 = 6;

Page 72: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Recursion

5!

(a) Sequence of recursive calls. (b) Values returned from each recursive call.

Final value = 120

5! = 5 * 24 = 120 is returned

4! = 4 * 6 = 24 is returned

2! = 2 * 1 = 2 is returned

3! = 3 * 2 = 6 is returned

1 returned

5 * 4!

1

4 * 3!

3 * 2!

2 * 1!

5!

5 * 4!

1

4 * 3!

3 * 2!

2 * 1!

Page 73: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

1

2 Recursive factorial function */

3 #include <stdio.h>

4

5 long factorial( long number ); /* function prototype */

6

7 /* function main begins program execution */

8 int main()

9 {

10 int i; /* counter */

11

12 /* loop 10 times. During each iteration, calculate

13 factorial( i ) and display result */

14 for ( i = 1; i <= 10; i++ ) {

15 printf( "%2d! = %ld\n", i, factorial( i ) );

16 } /* end for */

17

18 return 0; /* indicates successful termination */

19

20 } /* end main */

21

Page 74: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

1! = 1 2! = 2 3! = 6 4! = 24 5! = 120 6! = 720 7! = 5040 8! = 40320 9! = 36288010! = 3628800

22 /* recursive definition of function factorial */

23 long factorial( long number )

24 {

25 /* base case */

26 if ( number <= 1 ) {

27 return 1;

28 } /* end if */

29 else { /* recursive step */

30 return ( number * factorial( number - 1 ) );

31 } /* end else */

32

33 } /* end function factorial */

Page 75: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Example Using Recursion: The Fibonacci Series

Fibonacci series: 0, 1, 1, 2, 3, 5, 8...– Each number is the sum of the previous two – Can be solved recursively:

• fib( n ) = fib( n - 1 ) + fib( n – 2 )

– Code for the fibonacci functionlong fibonacci( long n ){if (n == 0 || n == 1) // base case

return n;else

return fibonacci( n - 1) + fibonacci( n – 2 );}

 

Page 76: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Example Using Recursion: The Fibonacci Series

f( 3 )

f( 1 )f( 2 )

f( 1 ) f( 0 ) return 1

return 1 return 0

return +

+return 

Page 77: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

1

2 Recursive fibonacci function */

3 #include <stdio.h>

4

5 long fibonacci( long n ); /* function prototype */

6

7 /* function main begins program execution */

8 int main()

9 {

10 long result; /* fibonacci value */

11 long number; /* number input by user */

12

13 /* obtain integer from user */

14 printf( "Enter an integer: " );

15 scanf( "%ld", &number );

16

17 /* calculate fibonacci value for number input by user */

18 result = fibonacci( number );

19

20 /* display result */

21 printf( "Fibonacci( %ld ) = %ld\n", number, result );

22

23 return 0; /* indicates successful termination */

24

25 } /* end main */

26

Page 78: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Enter an integer: 0Fibonacci( 0 ) = 0

Enter an integer: 1Fibonacci( 1 ) = 1

Enter an integer: 2Fibonacci( 2 ) = 1

Enter an integer: 3Fibonacci( 3 ) = 2

Enter an integer: 4Fibonacci( 4 ) = 3

27 /* Recursive definition of function fibonacci */

28 long fibonacci( long n )

29 {

30 /* base case */

31 if ( n == 0 || n == 1 ) {

32 return n;

33 } /* end if */

34 else { /* recursive step */

35 return fibonacci( n - 1 ) + fibonacci( n - 2 );

36 } /* end else */

37

38 } /* end function fibonacci */

Page 79: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Enter an integer: 5Fibonacci( 5 ) = 5

Enter an integer: 6Fibonacci( 6 ) = 8

Enter an integer: 10Fibonacci( 10 ) = 55

Enter an integer: 20Fibonacci( 20 ) = 6765

Enter an integer: 30Fibonacci( 30 ) = 832040

Enter an integer: 35Fibonacci( 35 ) = 9227465

Page 80: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Recursion vs. Iteration• Repetition

– Iteration: explicit loop– Recursion: repeated function calls

• Termination– Iteration: loop condition fails– Recursion: base case recognized

• Both can have infinite loops

• Balance – Choice between performance (iteration) and

good software engineering (recursion)

Page 81: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

GCD

else{

r=x%y;return (recgcd(y,r));

}

Output:Enter the two number 5 8G.C.D. of the 5 and 8 is 1

Page 82: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin
Page 83: Course Name:DATA STRUCTURES Course Code:10B11CI211 Course Credits:4 (3-1-2) Session:Jan – Jun 2013 Data Structures Team: Course Coordinator: Deepak, Nitin

Problems on recursion• Factorial• Fibonacci number generation• Fibonacci series generation• Reversing an integer number• Calculating power of a number• Prime Number checking• Generating prime number series• Calculating GCD of two numbers• Generating table of a number