Introduction to Data Structure

Noida Institute of Engineering and
Technology, Greater Noida
Introduction to Arrays and Linked List
Megha Gupta
Assistant Professor
Computer Science and
Engineering
Unit: 1
Data Structure
Course Details
(Ex: B Tech 3th Sem)

• Be familiar with basic techniques of algorithm analysis
• Be familiar with writing recursive methods
• Master the implementation of linked data structures such as linked lists
and binary trees
• Be familiar with advanced data structures such as balanced search
trees, hash tables, priority queues and the disjoint set union/find data
structure
• Be familiar with several sub-quadratic sorting algorithms including
quicksort, mergesort and heapsort
7/4/2020 Megha Gupta KCS 301: DS Unit 1 2
Course Objective

• Be familiar with some graph algorithms such as shortest path and
minimum spanning tree
• Master the standard data structure library of a major programming
language
• Master analyzing problems and writing program solutions to problems
using the above techniques
7/4/2020
Megha Gupta KCS 301: DS Unit 1
3
Course Objective

• CO 1 Describe how arrays, linked lists, stacks, queues, trees, and
graphs are represented in memory, used by the algorithms and
their common applications.
• CO 2 Identify the alternative implementations of data structures
with respect to its performance to solve a real world problem.
• CO 3 Understanding the concept of recursion, application of
recursion and its implementation and removal of recursion.
• CO 4 Discuss the computational efficiency of the sorting and
searching algorithms.
• CO 5 Implementation of Trees and Graphs and perform various
operations on these data structure.
Course Outcome

1.Engineering knowledge: Apply the knowledge of mathematics, science,
engineering fundamentals, and an engineering specialization for the
solution of complex engineering problems.
2.Problem analysis: Identify, formulate, research literature, and analyse
complex engineering problems reaching substantiated conclusions using
first principles of mathematics, natural sciences, and engineering
sciences.
3.Design/development of solutions: Design solutions for complex
engineering problems and design system components or processes that
meet the specified needs with appropriate consideration for public health
and safety, and cultural, societal, and environmental considerations.
4.Conduct investigations of complex problems: Use research based
knowledge and research methods including design of experiments,
analysis and interpretation of data, and synthesis of information to
provide valid conclusions.
Program Outcomes

5. Modern tool usage: Create, select, and apply appropriate techniques,
resources, and modern engineering and IT tools, including prediction and
modeling to complex engineering activities, with an understanding of the
limitations.
6. The engineer and society: Apply reasoning informed by the contextual
knowledge to assess societal, health, safety, legal and cultural issues and
the consequent responsibilities relevant to the professional engineering
practice.
7. Environment and sustainability: Understand the impact of the
professional engineering solutions in societal and environmental
contexts, and demonstrate the knowledge of, and need for sustainable
development.
8.Ethics: Apply ethical principles and commit to professional ethics and
responsibilities and norms of the engineering practice.
Program Outcomes

9. Individual and team work: Function effectively as an individual, and as
a member or leader in diverse teams, and in multidisciplinary settings.
10. Communication: Communicate effectively on complex engineering
activities with the engineering community and with the society at large,
such as, being able to comprehend and write effective reports and design
documentation, make effective presentations, and give and receive clear
instructions.
11. Project management and finance: Demonstrate knowledge and
understanding of the engineering and management principles and apply
these to one’s own work, as a member and leader in a team, to manage
projects and in multidisciplinary environments.
12. Life-long learning: Recognize the need for, and have the preparation
and ability to engage in independent and life-long learning in the
broadest context of technological change.
Program Outcomes

On successful completion of graduation degree the Computer Science &
Engineering graduates will be able to:
PSO1: The ability to design and develop the Hardware and Software
systems.
PSO2: An understanding of interdisciplinary computing techniques and an
ability to apply them in the design of advanced computing.
PSO3: An understanding of programming methodology software
development paradigms, design and analysis of Algorithms, Operating
Systems, Digital Logic Design, Theory of Computation, Discrete
Mathematics, Compiler Design, etc.
PSO4: The ability to integrate & manage the various phases/components
of software development projects of society.
Program Specific Outcomes

• PEO 1: To have an excellent scientific and engineering breadth so as
to comprehend, analyze, design and solve real-life problems using
state-of-the-art technologies.
• PEO 2: To lead a successful career in industries, to pursue higher
studies or to support entrepreneurial endeavors so that engineering
graduates can face the global challenges.
• PEO 3: To effectively bridge the gap between industry and academia
through effective communication skill, professional attitude, ethical
values and a desire to learn.
• PEO 4: To provide highly competitive environment and solidarity to
students for successful professional career as engineer, scientist,
entrepreneur and bureaucrats for the betterment of society.
Program Education Objectives

Sr.
No Course
Outcome
PO1
PO2
PO3
PO4
PO5
PO6
PO7
PO8
PO9
PO10
PO11
PO12
1 CO 1 3 3 3 3 3 2 1 1 3 2 2 1
2 CO 2 3 3 3 3 3 2 1 1 3 1 2 1
3 CO 3 3 3 3 3 3 2 1 1 3 1 2 1
4 CO 4 3 3 3 3 3 2 1 1 3 1 2 1
5 CO 5 3 3 3 3 3 2 1 1 3 1 2 1
CO-PO Mapping

Sr.
No Course Outcome
PSO1
PSO2
PSO3
PSO4
1 CO 1 3 2 3 3
2 CO 2 2 3 2 3
3 CO 3 2 2 3 2
4 CO 4 2 2 3 1
5 CO 5 3 1 3 2
CO-PSO Mapping

• Introduction: Basic Terminology, Elementary Data Organization,
Built in Data Types in C.
• Algorithm, Efficiency of an Algorithm, Time and Space Complexity,
Asymptotic notations: Big
• Oh, Big Theta and Big Omega, Time-Space trade-off. Abstract Data
Types (ADT)
• Arrays: Definition, Single and Multidimensional Arrays,
Representation of Arrays: Row Major
• Order, and Column Major Order, Derivation of Index Formulae for 1-
D,2-D,3-D and n-D Array
• Application of arrays, Sparse Matrices and their representations.
UNIT-1
Syllabus

• Linked lists: Array Implementation and Pointer Implementation of
Singly Linked Lists, Doubly
• Linked List, Circularly Linked List, Operations on a Linked List.
Insertion, Deletion, Traversal,
• Polynomial Representation and Addition Subtraction &
Multiplications of Single variable & Two
• variables Polynomial.
UNIT-1
Syllabus

Topics Duration (in
Hours)
Basic Terminology 1
Elementary Data Organization
Built in Data Types in C.
1
Algorithm, Efficiency of an Algorithm 1
Time and Space Complexity 1
Asymptotic notations: Big Oh, Big Theta and Big
Omega
1
Time-Space trade-off. 1
Abstract Data Types (ADT) 1
Arrays 1
Single and Multidimensional Arrays 1
Contents

Topics Duration (in
Hours)
Representation of Arrays: Row Major Order, and
Column Major Order
1
Derivation of Index Formulae for 1-D,2-D,3-D and n-D
Array
1
Sparse Matrices and their representations. 1
Representation of Arrays: Row Major Order, and
Column Major Order
1
Derivation of Index Formulae for 1-D,2-D,3-D and n-D
Array
1
Sparse Matrices and their representations. 1
Contents

Topics Duration (in
Hours)
Linked lists: Array Implementation
Pointer Implementation of Singly Linked Lists
1
Doubly Linked List 1
Circularly Linked List 1
Polynomial Representation 1
Contents

Objective of the course is to make students able to:
• Learn the basic types for data structure, implementation and
application.
• Know the strength and weakness of different data structures.
• Use the appropriate data structure in context of solution of given
problem
• Develop programming skills which require to solve given problem.
Objective of Unit

• Repetition statements (loops)-while, for, do-while statements, Loop
examples
• Functions-Designing Structured Programs, Functions, user defined
functions.
• Pointers – Introduction (Basic Concepts), Pointers for inter function
communication, pointers to pointers, compatibility, Pointer
Applications-Arrays and Pointers, Pointer Arithmetic and arrays,
Passing an array to a function, memory allocation functions, array
of pointers, programming applications.
• Basics of Structures, Arrays of Structures, Pointers to Structures,
Self-referential Structures.
• Dynamic Memory Allocation, Allocating Memory with malloc,
Allocating Memory with calloc, Freeing Memory, Reallocating
Memory Block
Prerequisite and Recap

Topic mapping with Course Outcome
7/4/2020 19
Array and Linked List(CO1)
Topic CO1 CO2 CO3 CO4 CO5
Array 1 - - - -
Linked List 1 - - - -

Basic Terminologies
• Data: are simply a value are set of values of different type which is
called data types like string, integer, char etc.
• Structure: Way of organizing information, so that it is easier to use.
• In simple words we can define DATA STRUCTURES as its a way
organizing data in such a way so that data can be easier to use.
Introduction

Definition
• Data Structure ..
A data structure is a particular way of organizing data in a computer
so that it can be used efficiently.
Introduction

Why Data Structure
Introduction

Why Data Structure
• Human requirement with computer are going to complex day by
day. To solve the complex requirements in efficient way we need
this study.
• Provide fastest solution of human requirements.
• Provide efficient solution of complex problem.
>Space
>Time
Introduction

Classification of Data Structure
Introduction

Classification of Data Structure ...
• Simple Data Structure / Primitive data structure: used to
represent the standard data types of any one of the computer
languages (integer, Character, float etc.).
• Compound Data Structure / Non Primitive Data Structure: can
be constructed with the help of any one of the primitive data structure
and it is having a specific functionality. It can be designed by user. It
can be classified as Linear and Non-Linear Data Structure.
Introduction

Classification of Data Structure ...
• Linear Data Structures: A linear data structure traverses the data
elements sequentially, in which only one data element can directly
be reached. Ex: Arrays, Linked Lists.
• Non-Linear Data Structures: Every data item is attached to
several other data items in a way that is specific for reflecting
relationships. The data items are not arranged in a sequential
structure. Ex: Trees, Graphs
Introduction

Operation on Linear/Non-Linear Data Structure
• Add an element
• Delete an element
• Traverse / Display
• Sort the list of elements
• Search for a data element
Introduction

Types of Linear Data Structure
• Array: An array is the collection of the variables of the same data
type that are referenced by the common name.
• int A[10], char B[10]
Introduction

Types of Linear Data Structure….
• Stack
Stack is a linear data structure in which the
insertion and deletion operations are performed
at only one end. In a stack, adding and removing
of elements are performed at a single position
which is known as “top”. That means, a new
element is added at top of the stack and an
element is removed from the top of the stack. In
stack, the insertion and deletion operations are
performed based on LIFO(Last In First Out)
principle.
Introduction

Types of Linear Data Structure…
• Queue is a linear data structure in which the
insertion and deletion operations are
performed at two different ends.
• The insertion is performed at one end and
deletion is performed at another end.
• In a queue data structure, the insertion
operation is performed at a position which is
known as “rear” and the deletion operation is
performed at a position which is known as
'front'.
• In queue data structure, the insertion and
deletion operations are performed based on
FIFO (First In First Out) principle.7/4/2020
30
Introduction

Types of Linear Data Structure…
• LINKED LIST
When we want to work with an unknown number of data values,
we use a linked list data structure to organize that data.
The linked list is a linear data structure that contains a sequence of
elements such that each element links to its next element in the
sequence. Each element in a linked list is called "Node".
Introduction

Types of NON Linear Data Structure
• Tree is a non-linear data
structure which organizes data in
hierarchical structure.
Introduction

Types of NON Linear Data Structure..
• Graph is a non-linear data structure. It
contains a set of points known as nodes
(or vertices) and a set of links known as
edges (or Arcs). Here edges are used to
connect the vertices.
• Generally, a graph G is represented as G
= ( V , E ), where V is set of
vertices and E is set of edges.
Introduction

What is an Array
• An array is the collection of the variable of the same type that are
referenced by the common name.
• An array is the derived data type.
• Consist of contiguous memory locations.
• Lowest address corresponds to first element while highest address
corresponds to last element.
• Can have data item of type int, float, char, double etc. also have
user derived data type like: structure, union.
Introduction to Array

Need for an Array
• To store large number of array of variables of same type under a
single variable.
• Eg.
To store Marks of 50 Students
Record of sales of 100 salesman

Types of Arrays in C
• In c programming language, arrays are classified into two types. They are
as follows...
> Single Dimensional Array / One Dimensional Array
> Multi Dimensional Array
Declaration of Single Dimensional Array
• datatype arrayName [ size ] ;
• int rollNumbers [60] ;
Initialization of Single Dimensional Array
• datatype arrayName [ size ] = {value1, value2, ...} ;
• int marks [6] = { 89, 90, 76, 78, 98, 86 } ;
• int marks [] = { 88,96,89, 90, 76, 78, 98, 86 } ;
Accessing Elements of Single Dimensional Array
A[2]=99;

• Array of an element of an array say “A[ I ]” is calculated using the
following formula:
• Address of A [ I ] = B + W * ( I – LB )
• Where,
B = Base address
W = Storage Size of one element stored in the array (in byte)
I = Subscript of element whose address is to be found
LB = Lower limit / Lower Bound of subscript, if not specified assume
0 (zero)

Example:
• Given the base address of an array B[1300…..1900] as 1020 and size
of each element is 2 bytes in the memory. Find the address
of B[1700].
• Solution:
The given values are: B = 1020, LB = 1300, W = 2, I = 1700
Address of A [ I ] = B + W * ( I – LB )
= 1020 + 2 * (1700 – 1300)
= 1020 + 2 * 400
= 1020 + 800
= 1820 [Ans]

• Find the base address of an array A[-15:65]. The size of each
element is 2 bytes in the memory and the location of A[37] is 4279.
Solution:
The given values are: LB = -15, UB = 65, W = 2, I = 37, A[37] = 4279
Address of A [ I ] = B + W * ( I – LB )
4279= B + 2 * (37 – (-15))
4279= B + 2 * 52
4279= B + 104
B= 4175 [Ans]

Creating an array in C
#include<stdio.h>
void main()
{
int a[10],i,n;
printf("nEnter number of elements");
scanf("%d",&n);
printf("n Enter %d elementsn",n);
for(i=0;i<n;i++){
scanf("%d",&a[i]);
}
for(i=0;i<n;i++){
printf("n%d",a[i]);
}
}

Passing array to function
• Passing array to function using call by value method.
• Passing array to function using call by reference.
• Passing entire array to a function as an argument.

Passing array to function using call by value method
#include <stdio.h>
void disp( char ch) {
printf("%c ", ch);
}
void main()
{
char arr[] = {'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'};
for (int x=0; x<10; x++) {
/* I’m passing each element one by one using subscript*/
disp (arr[x]);
}
}

Passing array to function using call by reference
#include <stdio.h>
void disp( int *num) {
printf("%d ", *num);
}
void main()
{
int arr[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 0};
for (int i=0; i<10; i++) {
/* Passing addresses of array elements*/
disp (&arr[i]);
}
}

Passing an entire array to a function
#include <stdio.h>
float average(float age[]);
int main()
{
float avg, age[] = {23.4, 55, 22.6, 3,
40.5, 18};
avg = average(age);
//Only name of an array is passed
//as an argument
printf("Average age = %.2f", avg);
return 0;
}
float average(float age[])
{
int i;
float avg, sum = 0.0;
for (i = 0; i < 6; ++i) {
sum += age[i];
}
avg = (sum / 6);
return avg;
}

Write a program in c to find max element in the array
using function.
#include <stdio.h>
#include <conio.h>
int max(int [],int);
void main()
{
int a[]={10,5,45,12,19};
int n=5,m;
clrscr();
m=max(a,n);
printf("nMAXIMUM NUMBER
IS %d",m);
getch();
}
int max(int x[],int k)
{
int t,i;
t=x[0];
for(i=1;i<k;i++)
{
if(x[i]>t)
t=x[i];
}
return(t);
}

Searching For an Element in an Array
• There are two ways to search an element:
Linear Search
> Check each element of an array.
> If the match found – element exists, else does not exist.
> Suitable for small lists since time consuming
> Suitable for unsorted Lists.
Binary Search
> Most Important preconditions is that the list should be
sorted.
> Suitable for arrays with long list of elements

Linear Search
• The linear search is a sequential search, which uses a loop to step
through an array, starting with the first element.
• It compares each element with the value being searched for, and stops
when either the value is found or the end of the array is encountered.
• If the value being searched is not in the array, the algorithm will
unsuccessfully search to the end of the array.

Advantages
• The linear search is simple - It is very easy to understand and
implement.
• It does not require the data in the array to be stored in any
particular order.
Disadvantages
• It has very poor efficiency because it takes lots of comparisons to
find a particular record in big files.
• The performance of the algorithm scales linearly with the size of
the input .
• Linear search is slower then other searching algorithms.

Linear Search Example

#include <stdio.h>
int search(int arr[], int n, int x) ;
void main( )
{ int arr[] = { 2, 3, 4, 10, 40 };
int x = 10;
int n = sizeof(arr) / sizeof(arr[0]);
int result = search(arr, n, x);
(result == -1) ? printf("Element is not present in array")
: printf("Element is present at index %d",
result);
}

int search(int arr[], int n, int x)
{
int i;
for (i = 0; i < n; i++)
if (arr[i] == x)
return i;
return -1;
}

Analysis of Linear Search
How long will our search take?
• In the best case, the target value is in the first element of the
array.
So the search takes some tiny, and constant, amount of time.
• In the worst case, the target value is in the last element of the
array.
So the search takes an amount of time proportional to the
length of the array. O(n)

Analysis of Linear Search
• In the average case, the target value is somewhere in the array.
• In fact, since the target value can be anywhere in the array, any
element of the array is equally likely.
• So on average, the target value will be in the middle of the array.
• So the search takes an amount of time proportional to half the
length of the array.

Binary Search
The general term for a smart search through sorted data is a binary
search.
1. The initial search region is the whole array.
2. Look at the data value in the middle of the search region.
3. If you’ve found your target, stop.
4. If your target is less than the middle data value, the new search
region is the lower half of the data.
5. If your target is greater than the middle data value, the new
search region is the higher half of the data.
6. Continue from Step 2.

Binary Search Example

#include <stdio.h>
void main()
{
int c, first, last, middle, n, search,
array[100];
printf("Enter number of
elements:n");
scanf("%d",&n);
printf("Enter %d integers:n", n);
for (c = 0; c < n; c++)
scanf("%d",&array[c]);
printf("Enter the value to find:n");
scanf("%d", &search);
first = 0;last = n - 1;
middle = (first+last)/2;
while (first <= last) {
if (array[middle] < search)
first = middle + 1;
else if (array[middle] == search)
{
printf("%d is present at index %d.n",
search, middle+1);
break;
}
else
last = middle - 1;
middle = (first + last)/2;
}
if (first > last)
printf("Not found! %d is not
present in the list.n", search); }
Binary Search Program

Time complexity of binary search
At each iteration, the array is divided by
half. So let’s say the length of array at any
iteration is n
At Iteration 1,
Length of array = n
At Iteration 2,
Length of array = n⁄2
At Iteration 3,
Length of array = (n⁄2)⁄2 = n⁄22
Therefore, after Iteration k,
Length of array = n⁄2k
Also, we know that after
After k divisions, the length
of array becomes 1
Therefore
Length of array = n⁄2k = 1
=> n = 2k
Applying log function on both
sides:
=> log2 (n) = log2 (2k)
=> log2 (n) = k log2 (2)
=> k = log2 (n)
Hence the time complexity of
Binary Search is
log2 (n)

Insert element in array
• Example
• Input
Input array elements: 10, 20, 30, 40, 50
Input element to insert: 35
Input position where to insert: 4
Output
Elements of array are: 10, 20, 30, 35, 40, 50

Logic to insert element in array
Insert an element at position 4.

Logic to insert element in array
for(i=size; i>=pos; i--)
arr[i] = arr[i - 1];

arr[pos - 1] = num;

Program to insert element in array
#include <stdio.h>
#define MAX_SIZE 100
int main()
{ int arr[MAX_SIZE];
int i, size, num, pos;
printf("Enter size of the array :
");
scanf("%d", &size);
printf("Enter elements in array
: ");
7/4/2020
70
for(i=0; i<size; i++)
scanf("%d", &arr[i]);
printf("Enter element to insert : ");
scanf("%d", &num);
printf("Enter the element position :
");
scanf("%d", &pos);
if(pos > size+1 || pos <= 0)
{ printf("Invalid position! Please
enter position between 1 to %d",
size);
}

else
{
/* Make room for new array
element by shifting to right */
for(i=size; i>=pos; i--)
{
arr[i] = arr[i-1];
}
/* Insert new element at given
position and increment size */
arr[pos-1] = num;
size++;
/* Print array after insert
operation */
printf("Array elements after
insertion : ");
{
printf("%dt", arr[i]);
}
}
return 0;
}

Delete element from an array
• Example
• Input
Input array elements: 10 20 30 40 50
Input position to delete: 2
Output
Array elements: 10, 30, 40, 50

Logic to remove element from array
•Step by step descriptive logic to
remove element from array.
•Move to the specified location
which you want to remove in given
array.
•Copy the next element to the
current element of array. Which is
you need to perform array[i] =
array[i + 1].
•Repeat above steps till last element
of array.
•Finally decrement the size of array
by one.

#include <stdio.h>
#define MAX_SIZE 100
int main()
{
int arr[MAX_SIZE];
int i, size, pos;
printf("Enter size of the array : ");
scanf("%d", &size);
printf("Enter elements in array : ");
{ scanf("%d", &arr[i]);
}
Program to delete an element from an array
printf("Enter the element position
to delete : ");
scanf("%d", &pos);
if(pos < 0 || pos > size)
{ printf("Please enter position
between 1 to %d", size);
}

else
{
for(i=pos; i<=size-1; i++){
arr[i-1] = arr[i];
}
size--;
}
printf("nElements of array after delete are : ");
for(i=0; i<size; i++) {
printf("%dt", arr[i]);
}
return 0;
}

Multi-dimensional Arrays in C
• Multidimensional array declaration
type name[size1][size2]...[sizeN];
• For example, the following declaration creates a three dimensional
integer array −
int threedim[5][10][4];

Two dimensional (2D) arrays
• An array of arrays is known as 2D array.
• The two dimensional (2D) array in C programming is also known
as matrix.
• A matrix can be represented as a table of rows and columns.

Initializing Two-Dimensional Arrays
• Multidimensional arrays may be initialized by specifying bracketed
values for each row. Following is an array with 3 rows and each row
has 4 columns.
int a[3][4] = {
{0, 1, 2, 3} , /* initializers for row indexed by 0 */
{4, 5, 6, 7} , /* initializers for row indexed by 1 */
{8, 9, 10, 11} /* initializers for row indexed by 2 */
};
• The nested braces, which indicate the intended row, are optional.
The following initialization is equivalent to the previous example −
int a[3][4] = {0,1,2,3,4,5,6,7,8,9,10,11};

Things that you must consider while initializing a 2D
array
• /* Valid declaration*/
int abc[2][2] = {1, 2, 3 ,4 }
• /* Valid declaration*/
int abc[][2] = {1, 2, 3 ,4 }
• /* Invalid declaration – you must specify second dimension*/
int abc[][] = {1, 2, 3 ,4 }
• /* Invalid because of the same reason mentioned above*/
int abc[2][] = {1, 2, 3 ,4 }

Accessing Two-Dimensional Array Elements
• An element in a two-dimensional array is accessed by using the
subscripts, i.e., row index and column index of the array.
For example : int val = a[2][3];
#include <stdio.h>
void main () {
int a[5][2] = { {0,0}, {1,2}, {2,4}, {3,6},{4,8}};
int i, j;
for ( i = 0; i < 5; i++ ) {
for ( j = 0; j < 2; j++ ) {
printf("a[%d][%d] = %dn", i,j, a[i][j] );
}
}
} 7/4/2020 Megha Gupta KCS 301: DS Unit 1 80

To store the elements entered by user in 2D Array
#include<stdio.h>
void main()
{
int abc[5][4];
int i, j;
for(i=0; i<5; i++) {
for(j=0;j<4;j++) {
printf("Enter value for abc[%d][%d]:", i, j);
scanf("%d", &abc[i][j]);
}
}
}7/4/2020 Megha Gupta KCS 301: DS Unit 1 81

Address Calculation in Two Dimensional Array:

Address of an element of any array say “A[ I ][ J ]” is calculated in two forms as
given:
Row Major System:
Address of A [ I1 ][ I2 ] = B + W * [( I1 – L1 ) * N2+ ( I2 – L2 )]
Column Major System:
Address of A [ I1 ][ I2 ] Column Major Wise = B + W * [( I1 – L1 ) + N1 * ( I2 – L2 )]
Where,
B = Base address
I1 = Row subscript of element whose address is to be found
I2 = Column subscript of element whose address is to be found
W = Storage Size of one element stored in the array (in byte)
L1 = Lower limit of row/start row index of matrix, if not given assume 0 (zero)
L2 = Lower limit of column/start column index of matrix, if not given assume 0
(zero)
N1 = Number of row of the given matrix
N2 = Number of column of the given matrix7/4/2020 Megha Gupta KCS 301: DS Unit 1 84

Q 1. An array X [-15……….10, 15……………40] requires one byte of storage. If
beginning location is 1500 determine the location of X [15][20].
As you see here the number of rows and columns are not given in the
question. So they are calculated as:
Number or rows say N1 = (U1 – L1) + 1 = [10 – (- 15)] +1 = 26
Number or columns say N2 = (U2 – L2) + 1 = [40 – 15)] +1 = 26
(i) Column Major Wise Calculation of above equation
The given values are: B = 1500, W = 1 byte, I1 = 15, I2 = 20, L1 = -15, L2 =
15, N1 = 26
Address of A [ I1 ][ I2 ] =B + W * [( I1 – L1 ) + N1 * ( I2 – L2 )]
= 1500 + 1 * [(15 – (-15)) + 26 * (20 – 15)] = 1500 + 1 * [30 + 26 * 5] =
1500 + 1 * [160] = 1660 [Ans]

Q 1. An array X [-15……….10, 15……………40] requires one byte of storage. If
beginning location is 1500 determine the location of X [15][20].
(ii) Row Major Wise Calculation of above equation
The given values are: B = 1500, W = 1 byte, I1 = 15, I2 = 20, L1 = -15, L2 =
15, N2 = 26
Address of A [ I1 ][ I2 ] =B + W * [( I1 – L1 )* N2 + ( I2 – L2 )]
= 1500 + 1* [26 * (15 – (-15))) + (20 – 15)] = 1500 + 1 * [26 * 30 + 5] =
1500 + 1 * [780 + 5] = 1500 + 785
= 2285 [Ans]

Three-Dimensional Array

Given an array [ 1..8, 1..5, 1..7 ] of integers. Calculate address of element
A[5,3,6], by using rows wise methods, if Base Address=900?
Solution:- The dimensions of A are :
N1=8 , N2=5, N3=7, I1=5, I2=3, I3=6, W=2,L1=1,L2=1,L3=1
Rows - wise :
Location (A[I1, I2, I3]) = B + W*[(E1N2+E2)*N3+E3]
= B + W*[((I1-L1)*N2+(I2-L2))*N3+(I3-L3)]
Location(A[5,3,6])= 900 + 2*[((5-1)*5+(3-1))*7+(6-1)]
= 900 + 2*[(4*5+2)*7+5]
= 900 +2*159
= 1218

Initializing Three-Dimensional Array
Method 1:
int x[2][3][4] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19, 20, 21, 22, 23};
Method 2:
int x[2][3][4] =
{
{ {0,1,2,3}, {4,5,6,7}, {8,9,10,11} },
{ {12,13,14,15}, {16,17,18,19}, {20,21,22,23} }
};

Applications of Arrays in C
● Arrays are used to Store List of values
● Arrays are used to Perform Matrix Operations
● Arrays are used to implement Search Algorithms
Linear Search Binary Search
● Arrays are used to implement Sorting Algorithms.
Insertion Sort Bubble Sort
Selection Sort Quick Sort Merge Sort, etc.,
● Arrays are used to implement Data structures.
Stack Using Arrays Queue Using Arrays
● Arrays are also used to implement CPU Scheduling Algorithms.

Sorting Using Array
Bubble Sort is the simplest sorting algorithm that works by
repeatedly swapping the adjacent elements if they are in wrong
order.
Bubble Sort

Bubble sort Illustration
Sorting Using Array

C Program for Bubble Sort
Sorting Using Array
// A function to implement
bubble sort
void bubbleSort(int arr[], int n)
{
int i, j;
for (i = 0; i < n-1; i++)
// Last i elements are already
in place
for (j = 0; j < n-i-1; j++)
if (arr[j] > arr[j+1])
swap(&arr[j], &arr[j+1]);
}
#include <stdio.h>
void swap(int *xp, int *yp)
{
int temp = *xp;
*xp = *yp;
*yp = temp;
}

// Driver program to test above
functions
int main()
{
int arr[] = {64, 34, 25, 12, 22, 11,
90};
int n = sizeof(arr)/sizeof(arr[0]);
bubbleSort(arr, n);
printf("Sorted array: n");
printArray(arr, n);
return 0;
}
C Program for Bubble Sort
Sorting Using Array
/* Function to print an array */
void printArray(int arr[], int size)
{
int i;
for (i=0; i < size; i++)
printf("%d ", arr[i]);
printf("n");
}

Insertion Sort Example
Sorting Using ArraySorting Using Array

Sorting Using Array

Sorting Using Array
#include <math.h>
#include <stdio.h>
/* Function to sort an array using
insertion sort*/
void insertionSort(int arr[], int n)
{
int i, key, j;
for (i = 1; i < n; i++) {
key = arr[i];
j = i - 1;
/* Move elements of arr[0..i-1],
that are
greater than key, to one
position ahead
of their current position */
while (j >= 0 && arr[j] >
key) {
arr[j + 1] = arr[j];
j = j - 1;
}
arr[j + 1] = key;
}
}

Sorting Using Array
// A utility function to print an array
of size n
void printArray(int arr[], int n)
{
int i;
for (i = 0; i < n; i++)
printf("%d ", arr[i]);
printf("n");
}
/* Driver program to test insertion
sort */
int main()
{
int arr[] = { 12, 11, 13, 5, 6 };
int n = sizeof(arr) /
sizeof(arr[0]);
insertionSort(arr, n);
printArray(arr, n);
return 0;
}

The selection sort algorithm sorts an array by repeatedly finding the
minimum element (considering ascending order) from unsorted part
and putting it at the beginning.
The algorithm maintains two subarrays in a given array.
1) The subarray which is already sorted.
2) Remaining subarray which is unsorted.
In every iteration of selection sort, the minimum element (considering
ascending order) from the unsorted subarray is picked and moved to
the sorted subarray.
Sorting Using Array
Selection Sort

Sorting Using Array
Selection Sort Example

Sorting Using Array
#include <stdio.h>
void swap(int *xp, int *yp)
{
int temp = *xp;
*xp = *yp;
*yp = temp;
}
void selectionSort(int arr[], int n)
{
int i, j, min_idx;
// One by one move boundary of
unsorted subarray
for (i = 0; i < n-1; i++)
{
// Find the minimum element
in unsorted array
min_idx = i;
for (j = i+1; j < n; j++)
if (arr[j] < arr[min_idx])
min_idx = j;
// Swap the found minimum
element with the first element
swap(&arr[min_idx], &arr[i]);
}
}
C Program for Selection Sort

Sparse Matrix
• Any matrix is called as Sparse Matrix in C, if it contains more
number of zeros.
• The mathematical formula behind this C Sparse Matrix is:
T >= (m * n )/2 where T is total number of zeros.
• Why to use Sparse Matrix instead of simple matrix ?
Storage: There are lesser non-zero elements than zeros
and thus lesser memory can be used to store only those elements.
Computing time: Computing time can be saved by
logically designing a data structure traversing only non-zero
elements..
• Sparse Matrix Representations
Triplet Representation (Array Representation)
Linked Representation

Triplet Representation (Array Representation)
• In this representation, we consider only non-zero values along
with their row and column index values. In this representation,
the 0throw stores total number of rows, total number of columns
and the total number of non-zero values in the sparse matrix.
For example, consider a matrix of size 5 X 6 containing 6
number of non-zero values. This matrix can be represented as
shown in the image.
7/4/2020
103

C Program that will convert 2D-representation to Sparse
representation.
#include <stdio.h>
void read_matrix(int a[10][10], int r,
int c);
void print_sparse(int b[20][3]);
void create_sparse(int a[10][10], int
r, int c, int b[20][3]);
void main() {
int a[10][10], b[20][3], r, c;
printf("nEnter the size of matrix
");
scanf("%d%d", &r, &c);
read_matrix(a, r, c);
create_sparse(a, r, c, b);
print_sparse(b);
}
void read_matrix(int a[10][10], int r, int c)
{
int i, j;
printf("nEnter elements of matrixn");
for (i = 0; i < r; i++) {
for (j = 0; j < c; j++) {
printf("[%d][%d]: ", i, j);
scanf("%d", &a[i][j]);
}
}
}

void create_sparse(int a[10][10], int r, int c, int b[MAX][3]) {
int i, j, k=1;
b[0][0] = r; b[0][1] = c;
for (i = 0; i < r; i++) {
for (j = 0; j < c; j++) {
if (a[i][j] != 0) {
b[k][0] = i;
b[k][1] = j;
b[k][2] = a[i][j];
k++;
}
}
b[0][2] = k - 1;
} }
void print_sparse(int b[MAX][3])
{
int i, c;
c = b[0][2];
printf("nSparse form - list of 3
triplesnn");
for (i = 0; i <= c; i++)
{
printf("%dt%dt%dn", b[i][0],
b[i][1], b[i][2]);
}
}

Linked Representation
In linked list, each node has four fields. These four fields are defined as:
• Row: Index of row, where non-zero element is located
• Column: Index of column, where non-zero element is located
• Value: Value of the non zero element located at index – (row ,
column)
• Next node: Address of the next node

Algorithms
• Algorithm is a step-by-step procedure, which defines a set of
instructions to be executed in a certain order to get the desired
output.
• Algorithms are generally created independent of underlying
languages, i.e. an algorithm can be implemented in more than
one programming language.
Introduction to Algorithms

Characteristics of an Algorithm
• Unambiguous − Algorithm should be clear and unambiguous. Each
of its steps (or phases), and their inputs/outputs should be clear
and must lead to only one meaning.
• Input − An algorithm should have 0 or more well-defined inputs.
• Output − An algorithm should have 1 or more well-defined
outputs, and should match the desired output.
• Finiteness − Algorithms must terminate after a finite number of
steps.
• Independent − An algorithm should have step-by-step directions,
which should be independent of any programming code

Example:
An algorithm to sum N
natural numbers.
Sum(A[],n)
{
s=0;
for(i=1 to n) do
s=s+A[i]
return s
}
An algorithm to add to matrix
Matrixadd(A[][],B[][],C[][],m,n)
{
for(i=1 to n) do
for(j=1 to n) do
c[i][j]=a[i][j]+b[i][j]
}

Algorithm for Insertion Sort
Insertion( A,n)
{
for(i=1 to n-1)
{
k=A[i]
j=i-1
while(j>0 && k< A[j])
{
A[j+1]= A[j]
j=j-1
}
A[j+1] = t
}
7/4/2020 Megha Gupta KCS 301: DS Unit 1
110

Performance analysis of an algorithm
• Space required to complete the task of that algorithm (Space
Complexity).
• Time required to complete the task of that algorithm (Time
Complexity)

Space Complexity
When we design an algorithm to solve a problem, it needs some
computer memory to complete its execution. For any algorithm,
memory is required for the following purposes...
1. To store program instructions.
2. To store constant values.
3. To store variable values.
4. And for few other things like function calls, jumping statements
etc,.
Total amount of computer memory required by an algorithm to
complete its execution is called as space complexity of that algorithm

Time Complexity
• Every algorithm requires some amount of computer time to
execute its instruction to perform the task. This computer time
required is called time complexity.
The time complexity of an algorithm can be defined as follows...
• The time complexity of an algorithm is the total amount of
time required by an algorithm to complete its execution.

Example 1
int sum(int a, int b)
{
return a+b;
}
Space Complexity –
In the above piece of code, it requires 2 bytes of memory to store
variable 'a' and another 2 bytes of memory is used for return value.
That means, totally it requires 4 bytes of memory to complete its
execution. And this 4 bytes of memory is fixed for any input value of 'a'.
This space complexity is said to be Constant Space Complexity.

Time Complexity –
• It requires 1 unit of time to calculate a+b and 1 unit of time to
return the value. That means, totally it takes 2 units of time to
complete its execution
• If any program requires a fixed amount of time for all input values
then its time complexity is said to be Constant Time Complexity.

Example 2
int sum(int A[ ], int n) {
int sum = 0, i;
for(i = 0; i < n; i++)
sum = sum + A[i];
return sum; }
In the above piece of code it requires
'n*2' bytes of memory to store array variable 'a[ ]'
2 bytes of memory for integer parameter 'n'
4 bytes of memory for local integer variables 'sum' and 'i' (2 bytes each)
2 bytes of memory for return value.
That means, totally it requires '2n+8' bytes of memory to complete its execution.
Here, the total amount of memory required depends on the value of 'n'. As 'n'
value increases the space required also increases proportionately. This type of
space complexity is said to be Linear Space Complexity.

If the amount of time required by an algorithm is increased with the
increase of input value then that time complexity is said to be Linear
Time Complexity.

Time Space Tradeoff

Asymptotic Notations
• Asymptotic analysis of an algorithm refers to defining the
mathematical boundation/framing of its run-time performance.
• Using asymptotic analysis, we can very well conclude the best case,
average case, and worst case scenario of an algorithm.
• Types of Asymptotic Notation
1. Big Oh(O)
2. Big Omega (Ω)
3. Theta (Θ)
4. Small Oh(o)
5. Small Omega (w)

Purpose of Asymptotic Notations
1. To simplify the running time of the function
2. To describe the behavior of the function.
3. To provide asymptotic bound.
4. To describe how the running time of an algorithm increases
with increase in input size

Big O Notation(O)
• It provide asymptotic upper bound (worst case running time ) to
a function.
O(g(n)) = { f(n): there exist positive constants c and n0 such that
0 <= f(n) <= c*g(n) for all n >= n0}

Q1 f(n) = 3n + 4, g(n) = n, Prove f(n) = O(g(n))
Sol.
To prove f(n) = O(g(n)) i.e. f(n) <= c.g(n)
It means 3n + 4 <=c.n
Let c= 5
n f(n) c.
g(n)
3n+4 5n
1 7 > 5
2 10 = 10
3 13 < 15
4 16 < 20
So, for n0 = 2
f(n) < = 5.g(n)
Hence f(n) = O(g(n))

Big Omega Notation(Ω)
• This notation is known as the lower bound of the algorithm, or a
Best Case of an algorithm.
Ω (g(n)) = {f(n): there exist positive constants c and n0 such that
0 <= c*g(n) <= f(n) for all n >= n0}.

Theta Notation(Θ)
• The theta notation bounds a functions from above and below, so
it defines exact asymptotic behavior.
Θ(g(n)) = {f(n): there exist positive constants c1, c2 and n0
such that 0 <= c1*g(n) <= f(n) <= c2*g(n) for all n >= n0}

Small o Notation(o)
• Small-o, commonly written as o, is an Asymptotic Notation to
denote the upper bound (that is not asymptotically tight) on the
growth rate of runtime of an algorithm.
o(g(n)) = { f(n): there exist positive constants c and n0 such that
0 <= f(n) < c*g(n) for all n >= n0}
• Another definition for o notation:
f(n) = o(g(n)) if and only if
lim(n→∞)f(n)/g(n)=0

Small omega Notation(w)
• Small-omega, commonly written as w, is an Asymptotic Notation
to denote the lower bound (that is not asymptotically tight) on
the growth rate of runtime of an algorithm.
w(g(n)) = { f(n): there exist positive constants c and n0 such that
f(n) > c*g(n)>=0 for all n >= n0}
• Another definition for o notation:
f(n) = o(g(n)) if and only if
lim(n→∞)g(n)/f(n)=0

Self Made Video Linked:
Youtube/other Video Links
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• https://www.youtube.com/watch?v=FEnwM-iDb2g&list=PLEbnTDJUr_IeHYw_sfBOJ6gk5pie0yP-0&index=2
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• https://www.youtube.com/watch?v=CZYR2v8rYLA&list=PLhb7SOmGNUc5AZurO-im4t_RDr-ymjz0d&index=3
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Faculty Video Links, Youtube & NPTEL
Video Links and Online Courses Details

Q.1 What is a data structure?
Q.2 What does abstract data type means?
Q.3 Explain about the types of linked lists
Q.4 Write an algorithm to merge two sorted arrays into a third array.
Do not sort the third array.
Q.5 What data structure would you mostly likely see in a non recursive
implementation of a recursive algorithm?
Q.6 List out the areas in which data structures are applied extensively?
Q.7 A two-dimensional array TABLE [6] [8] is stored in row major order
with base address 351. What is the address of TABLE [3] [4]?
Q.8 How do you find the complexity of an algorithm? What is the
relation between the time and space complexities of an algorithm?
Justify your answer with an example.
Daily Quiz

Question 1: Print Elements of a Matrix in Spiral Order Write a program that
reads an MxN matrix A and prints its elements in spiral order. You should start
from the element in the 0th row and 0th column in the matrix and proceed in a
spiral order as shown below.
Output for the above matrix: 1 2 3 4 8 12 16 15 14 13 9 5 6 7 11 10
Question 2: Write a program that reads an NxN square matrix M that
calculates the sum of the elements in individual rows, individual columns and
the two main diagonals. Among these sums, print the largest.
Consider the following matrix of order 3x3:
1 10 13
2 14 12
3 9 8
The row sum values are 1+10+13=24, 2+14+12=28 and 3+9+8=20. The
column sum values are 1+2+3=6, 10+14+9=33 and 13+12+8=33. The
diagonal sums are 1+14+8=23 and 13+14+3=30. The expected output is
maximum among these sums, which is 33.
Weekly Assignment

Weekly Assignment
Question 3: Write a program in C to count a total number of duplicate elements in an array.
Test Data :
Input the number of elements to be stored in the array :3
Input 3 elements in the array :
element - 0 : 5
element - 1 : 1
element - 2 : 1
Expected Output :
Total number of duplicate elements found in the array is : 1
Question 4.Write a program in C to merge two arrays of same size sorted in decending order.
Test Data :
Input the number of elements to be stored in the first array :3
element - 0 : 1
element - 1 : 2
element - 2 : 3
Input the number of elements to be stored in the second array :3
element - 0 : 1
element - 1 : 2
element - 2 : 3

1. In ........, search start at the beginning of the list and check every element in the list.
a. Binary search
b. Hash Search
c. Linear search
d. Binary Tree search.
2. To represent hierarchical relationship between elements, which data structure is suitable?
a. Graph
b. Tree
c. Dequeue
d. Priority Queue
3. Which of the following data structure is linear type?
a. Stack
b. Graph
c. Trees
d. Binary tree
4.Which of the following data structure can’t store the nonhomogeneous data elements?
a. Arrays
b. Stacks
c. Records
d. None of the above
MCQ s

MCQ s
5. Two main measures for the efficiency of an algorithm are
a. Processor and memory
b. Complexity and capacity
c. Time and space
d. Data and space
6. The Worst case occur in linear search algorithm when
a. Item is somewhere in the middle of the array
b. Item is not in the array at all
c. Item is the last element in the array
d. Item is the last element in the array or is not there at all
7. The complexity of Binary search algorithm is
a. O(n)
b. O(log )
c. O(n2)
d. O(n log n)
8. The complexity of linear search algorithm is
a. O(n)
b. O(log n)
c. O(n2)
d. O(n log n)

MCQ s
9. Arrays are best data structures
a. for relatively permanent collections of data
b. for the size of the structure and the data in the structure are constantly changing
c. for both of above situation
d. for none of above situation
10. Linked lists are best suited
a. for relatively permanent collections of data
b. for the size of the structure and the data in the structure are constantly changing
c. for both of above situation
d. for none of above situation

• https://drive.google.com/open?id=159ihlpBttJRK9pgu9OVIyCGJ8AC
fsZ1y
Old Question Papers

Expected Questions for University Exam
Q1. Assume the declaration of multi-dimensional arrays A and B to be,
A (-2:2, 2:22) and B (1:8, -5:5, -10:5)
(i) Find the length of each dimension and number of elements in A and B.
(ii) Find the address of element B (2, 2, 3), assuming Base address of B = 400
and there are W=4 words per memory location.
Q2. Write a program to insert a new element in the given unsorted array at kth
position.
Q3. Define data structure? What are the factors that influence the choice of particular
data structure?
Q4 . A 2 dimensional array DATA [-100:100,-5:50] is stored row major order with base
address 10. Calculate the address of DATA [99][49].
Q5 Explain Binary search and its limitations.
Q6 Write the difference between Linked list and array.

Introduction to List and LinkedLists
• List is a term used to refer to a linear collection of data items. A
List can be implemented either by using arrays or linked lists.
• Usually, a large block of memory is occupied by an array which
may not be in use and it is difficult to increase the size of an
array.
• Another way of storing a list is to have each element in a list
contain a field called a Linked or pointer, which contains the
address of the next element in the list.
• The successive elements in the list need not occupy adjacent
space in memory. This type of data structure is called a
linked list.
Introduction to Linked List

What are Linked Lists
A linked list is a lineardata structure.
Nodes make up linkedlists.
Nodes are structures made up of data and
a pointer to another node.
Usually the pointer iscalled next.

Linked List
• It is the most commonly used data structure used to store similar
type of data in memory.
• The elements of a linked list are not stored in adjacent
memory locations as in arrays.
• It is a linear collection of data elements, called nodes, where
the linear order is implemented by means of pointers.

Linked List
• In a linear or single-linked list, a node is connected to the next
node by a single Linked.
• A node in this type of linked list contains two types of fields
• data: which holds a list element
• next: which stores a Linked (i.e. pointer) to the next node in the
list.

Linked List
• The structure defined for a single linked list is implemented as
follows:
struct Node{
int info;
structNode * next;
}
• The structure declared for linear linked list holds two members
• An integer type variable ‘data’ which holds the elements and
• Another type ‘node’, which has next, which stores the
address of the next node in the list.

Figurative Representation

Properties of Linked list
• The nodes in a linked list are not stored contiguously in the
memory
• You don’t have to shift any element in the list
• Memory for each node can be allocated dynamically whenever
the need arises.
• The size of a linked list can grow or shrink dynamically

Operations on Linked List
• Creation:
• This operation is used to create a linked list
• Insertion / Deletion:
• At/From the beginning of the linked list
• At/From the end of the linked list
• At/From the specified position in a linked list
• Traversing:
• Traversing may be either forward or backward
• Searching:
• Finding an element in a linked list
• Concatenation:
• The process of appending second list to the end of the first list

Arrays Vs Linked Lists
Arrays Linked list
Fixed size: Resizing is expensive Dynamic size
Insertions and Deletions are
inefficient:
Elements are usually shifted
Insertions and Deletions are efficient:
No shifting
Random access i.e., efficient indexing No random access
Not suitable for operations
requiring accessing elements by
index such as sorting
No memory waste if the array is full
or almost full; otherwise may result
in much memory waste.
Since memory is allocated
dynamically(acc. to our need)
there is no waste of memory.
Sequential access is faster [Reason:
Elements in contiguous memory
locations]
Sequential access is slow [Reason:
Elements not in contiguous
memory locations]
Linked List

Types of Linked List
• Singly Linked List
• Doubly linked list
• Circular linked list
• Circular doubly linked list

Singly Linked List
• A singly linked list is a dynamic data structure which may grow
or shrink, and growing and shrinking depends on the operation
made.
• In this type of linked list each node contains two fields one is data
field which is used to store the data items and another is next
field that is used to point the next node in the list.
5 3 8 null
next next nextinfo info info

Creating a Linked List
• The head pointer is used to create and access unnamed nodes.
struct Node{
int info;
struct Node* next;
};
typedef struct
Node NodeType;
NodeType* head;
head=(NodeType *) malloc (sizeof( NodeType ) );
• The above statement obtains memory to store a node and
assigns its address to head which is a pointer variable.

Creating a Node
• Tocreate a new node, we use the malloc function to
dynamically allocate memory for the new node.
• After creating the node, we can store the new item in the node
using a pointer to that node.
• Note that p is not a node; instead it is a pointer to a
node.
Nodetype *p;
p=(NodeType *) malloc
(sizeof( NodeType ) ); p-
>info=50;
p->next = NULL;

Creating an empty list
void createEmptyList(NodeType *head)
{
head=NULL;
}
OR SIMPLY
NodeType *head =Null;

Inserting an Element
• While inserting an element or a node in a linked list, we have
to do following things:
• Allocate a node
• Assign a data to info field of the node.
• Adjust a pointer
• We can insert an element in following places
• At the beginning of the linked list
• At the end of the linked list
• At the specified position in a linked list

An algorithm to insert a node at the beginning of the singly
linked list
Let *head be the pointer to first node in the current list
1. Create a new node using mallocfunction
NewNode=(NodeType*)malloc(sizeof(Node
Type));
2. Assign data to the info field of newnode
NewNode->info=newItem;
3. Set next of new node tohead
NewNode->next=head;
4. Set the head pointer to the newnode
head=NewNode;
5. End

Insert A Node At The Beginning Of The Singly Linked List

Inserting a node at the beginning of the singly linkedlist

An algorithm to insert a node at the end of the singly linked
list
let *head be the pointer to first node in the current list
NewNode=(NodeType*)malloc(sizeof(NodeType));
3. Set next of new node toNULL
NewNode->next=NULL;
4. if (head ==NULL) then
Set head =NewNode.and exit.
5. Set temp=head;
6. while(temp->next!=NULL)
temp=temp->next; //increment temp
7. Set temp->next=NewNode;
8. End

An algorithm to insert a node at the end of the singly linked
list

An algorithm to insert a node after the given node in singly
linked list
let *head be the pointer to first node in the current list and *p be the
pointer to the node after which we want to insert a new node.
3. Set next of new node to next ofp
NewNode->next=p->next;
4. Set next of p to NewNode
p->next =NewNode
5. End

An algorithm to insert a node at the specified position in a
linked list
let *head be the pointer to first node in the current list
2. Assign data to the info field of new node
3. Enter position of a node at which you want to insert a new node.
Let this position is pos.
4. Set temp=head;
5. if (head ==NULL)then
printf(“void insertion”); and exit(1).
6. for(i=1; i<pos; i++)
temp=temp->next;
7. Set NewNode->next=temp->next;
set temp->next =NewNode..
8. End

Deleting Nodes
• A node may be deleted:
• From the beginning of the linked
list
• From the end of the linked list
• From the specified position in a
linked list

Deleting Nodes

Searching an item in a linkedlist
• Let *head be the pointer to first node in the current
list
1. If head==Null
Print “Empty List”
2. Else, enter an item to be searched askey
3. Set temp==head
4. While temp!=Null
If (temp->info == key)
Print “search success”
temp=temp->next;
5. If temp==Null
Print “Unsuccessful search”

What is circular linked list?
• Circular linked list is a variation of linked list in which the first
elements points to the next element and the last element
points to the first element.
• Both singly and doubly linked list can be made into a circular
linked list.
• Circular linked list can be used to help traverse the same list
again and again if needed.
Circular Linked List

Fun fact:
If you are worried about its implementation, then stop doing
that because instead of placing NULL at the last node’s address
field you are placing the address of very first node!

Circular linked list vs. Linear linked list
• A circularly linked list may be a natural option to represent arrays
that are naturally circular, e.g. the corners of a polygon, a pool
of buffers that are used and released in FIFO order, or a set of processes
that should be time-shared. In these applications, a pointer to any node
serves as a handle to the whole list.
• With a circular list, a pointer to the last node gives easy access also to
the first node, by following one Linked. Thus, in applications that
require access to both ends of the list, a circular structure allows one to
handle the structure by a single pointer, instead of two.
• The simplest representation for an empty circular list (when such a
thing makes sense) is a null pointer, indicating that the list has no
nodes. Without this choice, many algorithms have to test for this
special case, and handle it separately. By contrast, the use of null to
denote an empty linear list is more natural and often creates fewer
special cases.

Types of circular linked list
1. Singly: The last node points to the first node and there is only
Linked between the nodes of linked list.
2. Doubly: The last node points to the first node and there are
two links between the nodes of linked list.

Advantages of Circular linked lists
1. Any node can be a starting point. We can traverse the whole list
by starting from any point. We just need to stop when the first
visited node is visited again.
2. Circular lists are useful in applications to repeatedly go around
the list. For example: when multiple applications are running on
a PC, it is common for the operating system to put the running
applications on a list and then to cycle through them, giving each
of them a slice of time to execute, and then making them wait
while the CPU is given to another application. It is convenient for
the operating system to use a circular list so that when it reaches
the end of the list it can cycle around to the front of the list.
3. Circular Doubly Linked Lists are used for implementation of
advanced data structures like Fibonacci Heap.

Disadvantages of Circular linked list
1. Depending on the implementation, inserting at start of list would
require doing a search for last node which could be expensive.
2. Finding end of the list and loop control is harder ( no NULL’s to
mark the beginning and end).

Operations on singly circular linked list
• Insertion
• Deletion
• Display

Insertion
• Insertion can be of three types.
▫ Insert at first
▫ Insert at last
▫ Insert after constant
• Note: insertion after constant in circular and linear linked list
is exact same .

Insertion at first

Algorithm
• Start.
• Declare struct node *t.
• Set t:=start.
• Create a new node n by
malloc function and enter
the information in info part.
• Check if start=NULL set
start=n
set start->next=start. else
• Set n->next=start.
Program
void addfront()
{
struct node *t=start;
struct node *n=(struct
node*)malloc(sizeof(struct
node));
printf(“nenter the
information”); scanf(“%d”,&n-
>info);

Algorithm
• Repeat step(a)
while(t->next!=start)
▫ (a) set t:=t->next.
• [end of loop]
• Set t->next=n.
• Set start=n. [end if]
• Stop.
Program
if(start==NULL)
{
start=n;
start->next=start;
}
else
{
n->next=start; while(t-
>next!=start) t=t->next;
t->next=n;
start=n;
}

Insert at last

Algorithm
• Start.
• Declare struct node *t.
• Set t:=start.
• Create a new node n by
malloc function and enter
the information in info part.
• Check if start=NULL then,
set start:=n.
set start->next:=start.
Otherwise
• Set n->next:=start.
Program
void addlast()
{
struct node *n=(struct
node*)malloc(sizeof(struct
node));
printf(“nenter the
information”); scanf(“%d”,&n-
>info);

Algorithm
• Repeat step(a)
while(t!=NULL)
▫ (a) set t:=t->next.
• [end of loop]
• Set t->next=n. [end
if]
• Stop.
Program
if(start==NULL)
{
start=n;
start->next=start;
}
else
{
n->next=start;
while(t!=NULL) t=t-
>next;
t->next=n;
}

Deletion :
• Deletion can be of three types.
▫ Delete from front
▫ Delete from last
▫ Deletion from mid
• Note: deletion from mid in circular and linear linked list is exact
same .

Delete from front

Algorithm
start.
Check if (start=NULL) then,
print “empty list”
Check if
(start->next=start) then,
declare free (t)
set start:=NULL
otherwise
Repeat step(a) while(t-
>next!=start)
▫ (a) set t:=t->next
[end of loop]
void delfront()
{
struct node *t=start; if
(start==NULL)
printf (“nempty list”); else if
(start->next==start)
{
free (t);
start=NULL;
}
else
{
while(t->next!=start){
t=t->next;
Program

set start:=start->next
Declare free(t->next).
Set t->next:=start.
[end of if]
stop
start=start->next;
free(t->next);
t->next=start;
}
Continue…

Delete from last

Algorithm
• start.
• Check if (start=NULL) then,
print “empty list”
• Check if (start->next=start)
then,
declare free (t)
set start:=NULL
otherwise
• Repeat step(a)
while(t->next->next!=start)
▫ (a) set t:=t->next
• [end of loop]
• Declare free(t->next).
• Set t->next:=start.
• [end if]
• stop
Program
void dellast()
{
if (start==NULL)
printf(“nempty list”);
else if (start->next==start)
{
free (t);
start=NULL ;
}
else
{
while(t->next->next!=start)
t=t->next;
free(t->next);
t->next=start;
}
}

Display

Algorithm Program
• start.
• Set struct node
*t:=start.
• Check if(start=NULL) then,
print “empty list” otherwise
• Repeat step a and b
▫ (a) print t->info
▫ (b) set t:=t->next
• [end of loop]
• Print t->info [end if]
• stop
Void display()
{
if(start=NULL)
printf (“nempty list”);
else
{
{
printf(“%d”, t->info);
t=t->next;
}
printf(“%d”, t->info);
}
}

APPLICATIONS OF LINKED LIST
1.Applications that havean MRU list (a linked list of file names)
2. The cache in your browser that allows you to hit the BACK button (a
linked list ofURLs)
3. Undo functionality in Photoshopor Word (a linked list of state)
4. A stack, hash table, and binary tree can be implemented using a
doubly linkedlist.
Linked List

Doubly Linked List
Doubly linked list is a type of linked list in which each node apart from
storing its data has two links. The first Linked points to the previous
node in the list and the second Linked points to the next node in the
list. The first node of the list has its previous Linked pointing to NULL
similarly the last node of the list has its next node pointing to NULL.
Linked List
The two links help us to traverse the list in both backward and forward
direction. But storing an extra Linked requires some extra space.

First we define the node.
struct node
{
int data; // Data
node *prev; // A reference to the previous node
node *next; // A reference to the next node
};
Linked List

Important Points to be Remembered In double linked list, the first
node must be always pointed by head. Always the previous field of the
first node must be NULL. Always the next field of the last node must be
NULL
Linked List

Operations on Double Linked List
In a double linked list, we perform the following operations...
1. Insertion
2. Deletion
3. Display
Linked List

Insertion
In a double linked list, the insertion operation can be performed in
three ways as follows...
1. Inserting At Beginning of the list
2. Inserting At End of the list
3. Inserting At Specific location in the list
Linked List

Inserting At Beginning of the list
We can use the following steps to insert a new node at beginning of
the double linked list...
• Step 1 - Create a newNode with given value and newNode →
previous as NULL.
• Step 2 - Check whether list is Empty (head == NULL)
• Step 3 - If it is Empty then, assign NULL to newNode → next and
newNode to head.
• Step 4 - If it is not Empty then, assign head to newNode → next and
newNode to head.
Linked List

Inserting At End of the list
We can use the following steps to insert a new node at end of the
double linked list...
• Step 1 - Create a newNode with given value and newNode → next as
NULL.
• Step 3 - If it is Empty, then assign NULL to newNode → previous and
newNode to head.
• Step 4 - If it is not Empty, then, define a node pointer temp and
initialize with head.
• Step 5 - Keep moving the temp to its next node until it reaches to the
last node in the list (until temp → next is equal to NULL).
• Step 6 - Assign newNode to temp → next and temp to newNode →
previous.
Linked List

Inserting At Specific location in the list (After a Node)
We can use the following steps to insert a new node after a node in the double
linked list...
• Step 1 - Create a newNode with given value.
• Step 3 - If it is Empty then, assign NULL to both newNode → previous &
newNode → next and set newNode to head.
• Step 4 - If it is not Empty then, define two node pointers temp1 & temp2 and
initialize temp1 with head.
• Step 5 - Keep moving the temp1 to its next node until it reaches to the node
after which we want to insert the newNode (until temp1 → data is equal to
location, here location is the node value after which we want to insert the
newNode).
• Step 6 - Every time check whether temp1 is reached to the last node. If it is
reached to the last node then display 'Given node is not found in the list!!!
Insertion not possible!!!' and terminate the function. Otherwise move the
temp1 to next node.
• Step 7 - Assign temp1 → next to temp2, newNode to temp1 → next, temp1
to newNode → previous, temp2 to newNode → next and newNode to temp2
→ previous.
Linked List

Deletion
In a double linked list, the deletion operation can be performed in
three ways as follows...
1. Deleting from Beginning of the list
2. Deleting from End of the list
3. Deleting a Specific Node
Linked List

Deleting from Beginning of the list
We can use the following steps to delete a node from beginning of the
• Step 2 - If it is Empty then, display 'List is Empty!!! Deletion is not
possible' and terminate the function.
• Step 3 - If it is not Empty then, define a Node pointer 'temp' and
• Step 4 - Check whether list is having only one node (temp →
previous is equal to temp → next)
• Step 5 - If it is TRUE, then set head to NULL and delete temp (Setting
Empty list conditions)
• Step 6 - If it is FALSE, then assign temp → next to head, NULL to
head → previous and delete temp.
Linked List

Deleting from End of the list
We can use the following steps to delete a node from end of the
• Step 2 - If it is Empty, then display 'List is Empty!!! Deletion is not
• Step 3 - If it is not Empty then, define a Node pointer 'temp' and
• Step 4 - Check whether list has only one Node (temp → previous and
temp → next both are NULL)
• Step 5 - If it is TRUE, then assign NULL to head and delete temp. And
terminate from the function. (Setting Empty list condition)
• Step 6 - If it is FALSE, then keep moving temp until it reaches to the
last node in the list. (until temp → next is equal to NULL)
• Step 7 - Assign NULL to temp → previous → next and delete temp.
Linked List

Deleting a Specific Node from the list
We can use the following steps to delete a specific node from the
• Step 2 - If it is Empty then, display 'List is Empty!!! Deletion is not
• Step 3 - If it is not Empty, then define a Node pointer 'temp' and
• Step 4 - Keep moving the temp until it reaches to the exact node to
be deleted or to the last node.
• Step 5 - If it is reached to the last node, then display 'Given node not
found in the list! Deletion not possible!!!' and terminate the fuction.
• Step 6 - If it is reached to the exact node which we want to delete,
then check whether list is having only one node or not
Linked List

Step 7 - If list has only one node and that is the node which is to be
deleted then set head to NULL and delete temp (free(temp)).
• Step 8 - If list contains multiple nodes, then check whether temp is
the first node in the list (temp == head).
• Step 9 - If temp is the first node, then move the head to the next
node (head = head → next), set head of previous to NULL (head →
previous = NULL) and delete temp.
• Step 10 - If temp is not the first node, then check whether it is the
last node in the list (temp → next == NULL).
• Step 11 - If temp is the last node then set temp of previous of next
to NULL (temp → previous → next = NULL) and delete temp
(free(temp)).
• Step 12 - If temp is not the first node and not the last node, then set
temp of previous of next to temp of next (temp → previous → next =
temp → next), temp of next of previous to temp of previous (temp →
next → previous = temp → previous) and delete temp (free(temp)).
Linked List

Displaying a Double Linked List
We can use the following steps to display the elements of a double
linked list...
• Step 2 - If it is Empty, then display 'List is Empty!!!' and terminate
the function.
• Step 3 - If it is not Empty, then define a Node pointer 'temp' and
• Step 4 - Display 'NULL <--- '.
• Step 5 - Keep displaying temp → data with an arrow (<===>) until
temp reaches to the last node
• Step 6 - Finally, display temp → data with arrow pointing to NULL
(temp → data ---> NULL).
Linked List

• Polynomials
6 2 3 8
0 2
Index
represents
exponents
-3 18 0 0 23
0 42
•Array Implementation:
• p1(x) = 8x3 + 3x2 + 2x + 6
• p2(x) = 23x4 + 18x -3
p1(x) p2(x)
Linked List

•This is whyarrays aren’tgood to represent polynomials:
• p3(x) = 16x21 - 3x5 + 2x +6
6 2 0 0 -3 0 ………… 0 16
WASTE OF SPACE!
Linked List

•Advantages of using anArray:
• only good for non-sparsepolynomials.
• ease of storage andretrieval.
•Disadvantages of using anArray:
• havetoallocate arraysize ahead of time.
• huge array size required for sparse polynomials. Waste of
space andruntime.
Linked List

• Polynomial Representation
• Linked list Implementation:
• p1(x) = 23x9 + 18x7 + 41x6 + 163x4 + 3
• p2(x) = 4x6 + 10x4 + 12x + 8
23 9 18 7 41 6 18 7 3 0
4 6 10 4 12 1 8 0
P1
P2
NODE (contains coefficient &exponent)
TAIL (contains pointer)
7/4/2020
209
Linked List

•Advantages of using a Linkedlist:
savespace (don’t have toworryaboutsparse polynomials) and easy to
maintain
don’t need toallocate list size and can declare nodes (terms) only as
needed
•Disadvantages of using a Linked list :
can’t go backwards through thelist
can’t jump to the beginning of the listfrom theend.
Linked List

Polynomials
A(x)
em 1
am 1x am
em 2 e0
2 x ... a0 x
Representation
struct polynode {
int coef;
int exp;
struct polynode * next;
};
typedef struct polynode *polyptr;
coef exp next
Linked List

Adding polynomials using a Linkedlist
representation: (storing the result inp3)
Todo this, we haveto break the process down to cases:
• Case 1: exponent of p1 > exponent ofp2
Copy node of p1 to end ofp3. [go to nextnode]
• Case 2: exponent of p1 < exponent ofp2
Copy node of p2 to end ofp3. [go to nextnode]
• Case 3: exponent of p1 = exponent ofp2
Create a new node in p3 with the same exponent and with the sum of
the coefficients of p1 andp2.
Linked List

Example
3 14 2 8
a
8 14 -3 10
b
b
1 0 null
10 6 null
8x14
3x10
10x 6
a 3x14
2x8
1
Linked List

Adding Polynomials
3 14
a
8 14
2 8
-3 10
1 0
10 6
b
11 14
d
a->expon == b->expon
3 14 1 0
a
2 8
-3 10 10 6
b
8 14
11 14 -3 10 a->expon < b->expon
Linked List

3 14 2 8 1 0
a
8 14 -3 10 10 6
b
11 14 -3 10
d
a->expon > b->expon
2 8
Linked List

Q1. What is the output of following function for start pointing to first node of
following linked list? 1->2->3->4->5->6
void fun(struct node* start)
{
if(start == NULL)
return;
printf("%d ", start->data);
if(start->next != NULL )
fun(start->next->next);
printf("%d ", start->data);
}
Q2. What type of memory allocation is referred for Linked lists?
Daily Quiz

Q3. Describe what is Node in Linked list? And name the types of Linked Lists?
Q4. Mention what is the difference between Linear Array and Linked List?
Q5. Mention what are the applications of Linked Lists?
Q6. What does the dummy header in linked list contain?
Q7. Mention what is the difference between singly and doubly linked lists?
Q8. Mention what is the biggest advantage of linked lists?
Q9. Mention how to insert a new node in linked list where free node will be
available?
Daily Quiz

Weekly Assignment
Q1. Assume that the structure of a Linked List node is as follows:
struct node {
int data;
struct node *next;
}; What does the following function print for a given Linked List which
has elements in the order 1->2->3->4->5->6. Explain your answer.
1. void fun(struct node* head){
2. if(head == NULL)
3. return;
4. printf("%d ", head->data);
5. if(head->next != NULL )
6. fun(head->next->next);
7. printf("%d ", head->data);
8. }

Weekly Assignment
Q2. Write a C Program to reverse the Linked list
Q3. Write a C Program to merge two Linked list.
Q4. Write a C Program to alternate print the content of the list.
Q5. Write a program for printing the following in a given linked list:
a. Maximum
b. Minimum

Weekly Assignment
Q6. Print the sum of all even numbers stored in a circular linked list.
Q7. Take N numbers as input from the user and create a doubly linked
list.
Q 8. Find the smallest number in the doubly linked list.
Q 9. Delete the smallest number in the doubly linked list.
Q 10. Write the C Program to add all even number in the list.

1. What does the following function do for a given Linked List with first
node as head?
void fun1(struct node* head)
{
if(head == NULL)
return;
fun1(head->next);
printf("%d ", head->data);
}
A Prints all nodes of linked lists
B Prints all nodes of linked list in reverse order
C Prints alternate nodes of Linked List
D Prints alternate nodes in reverse order
MCQ s

2. Which of the following points is/are true about Linked List data
structure when it is compared with array
A Arrays have better cache locality that can make them better in terms
of performance.
B It is easy to insert and delete elements in Linked List
C Random access is not allowed in a typical implementation of Linked
Lists
D The size of array has to be pre-decided, linked lists can change their
size any time.
E All of the above
MCQ s

MCQ s
3. Which of the following sorting algorithms can be used to sort a
random linked list with minimum time complexity?
A Insertion Sort
B Quick Sort
C Heap Sort
D Merge Sort
4. In the worst case, the number of comparisons needed to search a
singly linked list of length n for a given element is (GATE CS 2002)
A log 2 n
B n/2
C log 2 n – 1
D n

MCQ s
5. Is it possible to create a doubly linked list using only one pointer with
every node.
A Not Possible
B Yes, possible by storing XOR of addresses of previous and next nodes.
C Yes, possible by storing XOR of current node and next node
D Yes, possible by storing XOR of current node and previous node
6. You are given pointers to first and last nodes of a singly linked list,
which of the following operations are dependent on the length of the
linked list?
A Delete the first element
B Insert a new element as a first element
C Delete the last element of the list
D Add a new element at the end of the list

MCQ s
7. Consider the following function to traverse a linked list.
void traverse(struct Node *head) {
while (head->next != NULL)
{
printf("%d ", head->data);
head = head->next;
}
}
Which of the following is FALSE about above function?
A The function may crash when the linked list is empty
B The function doesn't print the last node when the linked list is not
empty
C The function is implemented incorrectly because it changes head

MCQ s
8. Let P be a singly linked list. Let Q be the pointer to an intermediate
node x in the list. What is the worst-case time complexity of the best
known algorithm to delete the node x from the list?
A O(n) B O(log2 n)
C O(logn) D O(1)
9. The concatenation of two lists is to be performed in O(1) time. Which
of the following implementations of a list should be used?
A singly linked list
B doubly linked list
C circular doubly linked list
D array implementation of lists
10. In a doubly linked list, the number of pointers affected for an
insertion operation will be
A 4 B 0 C 1 D None of these

Expected Questions for University Exam
Q1. Write a program in c to delete a specific element in single linked list.
Double linked list takes more space than single linked list for storing one extra
address. Under what condition, could a double linked list more beneficial than
single linked list.
Q2. What is a doubly linked list? How is it different from the single linked list?
Q3. What are the advantages and disadvantages of array over linked list?
Q4 . Write a program to implement linear linked list, showing all the
operations that
can be performed on a linked list.
Q5. Implement Doubly Circular Linked list and insert an element at a given
position in the doubly circular Linked list.

https://drive.google.com/open?id=15fAkaWQ5c
cZRZPzwlP4PBh1LxcPp4VAd
Old Question Papers

Summary
Each data structure has strengths and weaknesses which affect
performance depending on the task.
Arrays allow random access and require less memory per element
(do not need space for pointers) while lacking efficiency for
insertion/deletion operations and memory allocation.
On the contrary, linked lists are dynamic and have faster
insertion/deletion time complexities.
However, linked list have a slower search time and pointers require
additional memory per element in the list.

References
[1] Aaron M. Tenenbaum, Yedidyah Langsam and Moshe J. Augenstein,
“Data Structures Using C and C++”, PHI Learning Private Limited, Delhi
India
[2] Horowitz and Sahani, “Fundamentals of Data Structures”, Galgotia
Publications Pvt Ltd Delhi India.
[3] Lipschutz, “Data Structures” Schaum’s Outline Series, Tata McGraw-
hill Education (India) Pvt. Ltd.
[4] Thareja, “Data Structure Using C” Oxford Higher Education.
[5] AK Sharma, “Data Structure Using C”, Pearson Education India.

Thank you

Introduction to Data Structure

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