Data Structure is a comprehensive and student-friendly textbook that provides a strong foundation in organizing and managing data efficiently for programming and problem-solving. The book introduces fundamental concepts such as arrays, pointers, abstract data types, and algorithm analysis, helping learners understand how data is structured and processed in computer systems.
It covers essential topics including linear data structures, sorting and searching techniques, linked lists, stacks, and queues, along with their implementation and real-world applications. The book also explores advanced structures such as trees and graphs, including their representations, traversals, and practical uses in computing.
The content is presented in a clear, structured, and application-oriented manner, supported by diagrams, examples, and exercises to enhance conceptual understanding and practical skills. This book serves as a valuable resource for students and learners aiming to build strong programming logic and develop expertise in data organization and algorithmic problem-solving.
1. Introduction to Data Structures
1.1 Array, Types of Array and Its Representation
1.1.1 Definition and Syntax of Arrays
1.1.2 Real-Life Examples
1.1.3 Features of Arrays
1.1.4 Declaration and Initialization
1.1.5 Types of Arrays
1.1.6 Applications of Arrays
1.1.7 Advantages and Limitation of Arrays
1.2 Self-Referential Structure
1.2.1 Definition and syntax
1.2.2 Applications of Self-Referential Structures
1.2.3 Advantages and Limitation
1.3 Pointer and Dynamic Memory Allocation
1.3.1 Declaration, Initialization, and Dereferencing
1.3.2 Uses of Pointers
1.3.3 Dynamic Memory Allocation
1.3.4 Complete Example
1.3.5 Advantages and Disadvantage of Pointers and Dynamic Memory
1.4 Data Types, Data Objects and Abstract Data Type (ADT)
1.4.1 Definition of Data and Information
1.4.2 Data Types
1.4.3 Definition of Data Objects
1.4.4 Abstract Data Type (ADT)
1.5 Data Structure and Types of Data Structure
1.5.1 Defintion and Importance
1.5.2 Classification of Data Structures
1.5.3 Differences Between Linear and Non-Linear Data Structures
1.5.4 Applications of Data Structures
1.6 Algorithm Analysis: Space Complexity, Time Complexity, and Asymptotic
1.6.1 Characteristics and Structure of Algorithm
1.6.2 Space and Time Complexity
1.6.3 Examples of Time Complexities
1.6.4 Difference between time complexity and space complexity
1.6.5 Time Complexity Classes with Examples
1.6.6 Best, Average, and Worst Case Analysis
1.6.7 Asymptotic Notations (O, Ω, Θ)
2. Linear Data Structure
2.1 Introduction to Linear Data Structure
2.1.1 Definition of Liner Data Structure
2.1.2 Characteristics of Linear Data Structures
2.1.3 Types of Linear Data Structures
2.1.4 Applications of Linear Data Structures
2.1.5 Advantages of Linear Data Structures
2.2 Sorting Algorithms with Time Complexity
2.2.1 Definition of Sorting
2.2.2 Types of Sorting
2.2.3 Objectives of Sorting
2.2.4 Bubble Sort
2.2.5 Insertion Sort
2.2.6 Selection Sort
2.2.7 Merge Sort
2.2.8 Quick Sort
2.2.9 Time and Space Complexity of Sorting Algorithms
2.3 Searching
2.3.1 Linear Search (Sequential Search)
2.3.2 Binary Search
2.3.3 Comparison of Searching Methods
3. Linked List
3.1 Introduction to Linked List
3.2 Implementation of Linked List
3.3 Types of Linked Lists
3.3.1 Singly Linked List
3.3.2 Doubly Linked List
3.3.3 Circular Singly Linked List (CSLL)
3.3.4 Circular Doubly Linked List (CDLL)
4. Stack and Queue
4.1 Introduction to Stack
4.1.1 Concept and Characteristics (LIFO)
4.1.2 Characteristics of LIFO
4.1.3 Basic Operations on Stack
4.2 Stack Implementation
4.2.1 Static representation using arrays
4.2.2 Advantages of Static Implementation
4.2.3 Dynamic representation using linked lists
4.4 Applications of Stacks
4.5 Evaluation and Conversion of Expresssions - Infix, Prefix, Postfix
4.5.1 Algorithm to Convert Infix Expression to Postfix Expression
4.5.2 Algorithm to Convert Postfix Expression Infix to Expression
4.6 Introduction to Queue
4.6.1 Basic Term Related to Queue
4.6.2 Operations on Queue
4.6.3 Advantages and Disadvantages of Queue
4.6.4 Applications Queue
4.7 Representation of Queue - Static & Dynamic
4.7.1 Static representation using arrays
4.7.2 Dynamic representation using Linked List
4.8 Primitive Operations on Queue (Insert, Delete, Display)
4.8.1 Types of Queue
4.9 Circular Queue (Insert, Delete, Display)
5. Tree and Graph
5.1 Tree Concept & Terminologies
5.1.1 Definition
5.1.2 Terminologies Used InTree Data Structure
5.2 Binary Tree, Binary Search Tree
5.2.1 Binary Tree
5.2.2 Types of Binary Tree
5.3 Operations on BT and BST (Create, Insert, Delete)
5.3.1 Operations on Binary Tree
5.4 Tree Traversals (Preorder, Inorder, Postorder)
5.4.1 Binary Search Tree (BST)
5.5 Height Balanced Tree - AVL Trees - Rotations
5.5.1 AVL trees –Rotations
5.5.2 AVL tree examples
5.6 Introduction of Graph
5.6.1 Types of Graph
5.6.2 Basic Terminologies Related to Graph
5.6.3 Applications of Graph
5.7 Representation of Graph - Adjacency Matrix, Adjacency List
5.7.1 Adjacency Matrix
5.7.2 Adjacency List
5.8 Graph Traversals- BFS and DFS
5.8.1 Depth-First Search (DFS)
5.8.2 Breadth-First Search (BFS)
5.9 Degree of Graph
5.10 Spanning Tree
5.10.1 Properties of Spanning Tree
5.10.2 Minimum Spanning Tree
5.10.3 Applications of Spanning Tree
BBA-CA | Second Year
Semester – III, Major Mandatory (7)
This textbook is aligned with the revised syllabus as outlined by the National Education Policy 2020 (NEP 2020) for the Faculty of Commerce and Management, Bachelor of Business Administration in Computer Application (BBA-CA), effective from June 2025.
