Basic Concepts in Data Structures
By K.Meenendranath Reddy and S. Reshma
()
About this ebook
Data structures are a specific way of organizing data in a specialized format on a computer so that the information can be organized, processed, stored, and retrieved quickly and effectively.
Read more from K.Meenendranath Reddy
Design of Electrical Circuits using Engineering Software Tools Rating: 0 out of 5 stars0 ratingsDesign Thinking for Strategic Innovation Rating: 0 out of 5 stars0 ratings
Related to Basic Concepts in Data Structures
Related ebooks
Mastering Data Structures: Core Concepts and Principles Rating: 0 out of 5 stars0 ratingsData Structure and Algorithms in Java: From Basics to Expert Proficiency Rating: 0 out of 5 stars0 ratingsCoding In C Decoded: Decoded, #1 Rating: 0 out of 5 stars0 ratingsMastering C: A Comprehensive Guide to Programming Excellence Rating: 0 out of 5 stars0 ratingsMastering C++ Swiftly Rating: 0 out of 5 stars0 ratingsAlgorithms Unlocked: Mastering Computational Problem Solving Rating: 0 out of 5 stars0 ratingsIntroduction to programming in C, a practical approach. Rating: 0 out of 5 stars0 ratingsData Structures II Essentials Rating: 0 out of 5 stars0 ratingsRust Mini Reference: A Hitchhiker's Guide to the Modern Programming Languages, #5 Rating: 0 out of 5 stars0 ratings300+ Python Algorithms: Mastering the Art of Problem-Solving Rating: 5 out of 5 stars5/5C & Data Structures Rating: 0 out of 5 stars0 ratingsMastering C: A Comprehensive Guide to Proficiency in The C Programming Language Rating: 0 out of 5 stars0 ratingsC++ Programming: From Novice to Expert in a Step-by-Step Journey Rating: 0 out of 5 stars0 ratingsData Structure in Python: From Basics to Expert Proficiency Rating: 0 out of 5 stars0 ratingsNew Learning of Python by Practical Innovation and Technology Rating: 0 out of 5 stars0 ratingsMastering C: Advanced Techniques and Tricks Rating: 0 out of 5 stars0 ratingsEmbedded Systems Programming with C++: Real-World Techniques Rating: 0 out of 5 stars0 ratingsMastering Racket Programming: From Basics to Expert Proficiency Rating: 0 out of 5 stars0 ratingsCUDA Programming with Python: From Basics to Expert Proficiency Rating: 1 out of 5 stars1/5Mastering Rust: The Ultimate Starter Guide Rating: 0 out of 5 stars0 ratingsRust for C++ Programmers: Learn how to embed Rust in C/C++ with ease (English Edition) Rating: 0 out of 5 stars0 ratingsLinux System Programming: From Basics to Expert Proficiency Rating: 0 out of 5 stars0 ratingsC++ Programming Cookbook Rating: 0 out of 5 stars0 ratingsLearning Advanced Programming Rating: 0 out of 5 stars0 ratingsLearning AWS Lumberyard Game Development Rating: 0 out of 5 stars0 ratings
Computers For You
The ChatGPT Millionaire Handbook: Make Money Online With the Power of AI Technology Rating: 4 out of 5 stars4/5Elon Musk Rating: 4 out of 5 stars4/5Mastering ChatGPT: 21 Prompts Templates for Effortless Writing Rating: 4 out of 5 stars4/5How to Create Cpn Numbers the Right way: A Step by Step Guide to Creating cpn Numbers Legally Rating: 4 out of 5 stars4/5Procreate for Beginners: Introduction to Procreate for Drawing and Illustrating on the iPad Rating: 5 out of 5 stars5/5Alan Turing: The Enigma: The Book That Inspired the Film The Imitation Game - Updated Edition Rating: 4 out of 5 stars4/5CompTIA Security+ Get Certified Get Ahead: SY0-701 Study Guide Rating: 5 out of 5 stars5/5Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics Rating: 4 out of 5 stars4/5Deep Search: How to Explore the Internet More Effectively Rating: 5 out of 5 stars5/5SQL QuickStart Guide: The Simplified Beginner's Guide to Managing, Analyzing, and Manipulating Data With SQL Rating: 4 out of 5 stars4/5Excel 101: A Beginner's & Intermediate's Guide for Mastering the Quintessence of Microsoft Excel (2010-2019 & 365) in no time! Rating: 0 out of 5 stars0 ratingsEverybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are Rating: 4 out of 5 stars4/5Creating Online Courses with ChatGPT | A Step-by-Step Guide with Prompt Templates Rating: 4 out of 5 stars4/5The Technological Republic: Hard Power, Soft Belief, and the Future of the West Rating: 0 out of 5 stars0 ratingsThe Hacker Crackdown: Law and Disorder on the Electronic Frontier Rating: 4 out of 5 stars4/5The Self-Taught Computer Scientist: The Beginner's Guide to Data Structures & Algorithms Rating: 0 out of 5 stars0 ratingsCompTia Security 701: Fundamentals of Security Rating: 0 out of 5 stars0 ratingsCompTIA IT Fundamentals (ITF+) Study Guide: Exam FC0-U61 Rating: 0 out of 5 stars0 ratingsThe Professional Voiceover Handbook: Voiceover training, #1 Rating: 5 out of 5 stars5/5What Video Games Have to Teach Us About Learning and Literacy. Second Edition Rating: 4 out of 5 stars4/5The Insider's Guide to Technical Writing Rating: 0 out of 5 stars0 ratingsData Analytics for Beginners: Introduction to Data Analytics Rating: 4 out of 5 stars4/5Slenderman: Online Obsession, Mental Illness, and the Violent Crime of Two Midwestern Girls Rating: 4 out of 5 stars4/5A Quickstart Guide To Becoming A ChatGPT Millionaire: The ChatGPT Book For Beginners (Lazy Money Series®) Rating: 4 out of 5 stars4/5A Brief History of Artificial Intelligence: What It Is, Where We Are, and Where We Are Going Rating: 4 out of 5 stars4/5Going Text: Mastering the Command Line Rating: 4 out of 5 stars4/5
Related categories
Reviews for Basic Concepts in Data Structures
0 ratings0 reviews
Book preview
Basic Concepts in Data Structures - K.Meenendranath Reddy
INDEX
CHAPTER-1: DATA STRUCTURES 1
1.1 Introduction to Data Structures 1
1.1.1 Definition 1
1.1.2 Importance of Data Structures 1
1.1.3 Classification of Data Structures 2
1.1.4 Applications of Data Structures 4
1.1.5 Advantages of Data Structures 4
Abstract Data Types (ADTs) 5
1.2.1 ADT 5
1.2.2 Specifications of ADTs 6
1.2.3 Features of ADT 6
1.2.4 Advantages 7
1.2.5 Disadvantages 7
1.3 Arrays 8
1.3.1 Characteristics of an Array 8
1.3.2 Array Types 9
1.3.3 Advantages of Arrays 11
1.3.4 Disadvantages of Arrays 11
1.4 Searching Techniques 12
1.5 Sorting Techniques 15
CHAPTER-2: LINKED LISTS 18
2.1 Linked Lists 18
2.1.1 Representation of Linked List in Memory 18
2.2 Types of Linked Lists 19
2.2.1. Single Linked List (SLL) 19
2.2.2. Circular Linked List (CLL) 23
2.2.3. Double Linked List 26
2.3 Comparison between Array and Linked List 30
2.4 Applications of Linked List 31
CHAPTER-3: STACKS 32
3.1 Stacks 32
3.2 Representation of Stack 32
3.2.1. Array Representation of a Stack 33
3.2.2. Linked List Representation of a Stack 35
3.3 Applications of Stack 37
3.3.1. Factorial Calculation 38
3.3.2. Infix to Postfix Conversion 38
3.3.3. Evaluation of Postfix Expression 40
3.3.4. Reversing List of Elements 41
CHAPTER-4: QUEUES & DEQUES 42
4.1 Queues 42
4.2 Representation of Queue 42
4.2.1. Representation of Queue Using Arrays 42
4.2.2. Representation of Queue Using Linked List 45
4.3 Various Queue Structures 50
4.3.1. Circular Queues 50
4.3.2. Deque 52
CHAPTER-5: TREES 56
5.1 Basic Terminology 56
5.2 Tree 58
5.3 Binary Tree 58
5.3.1 Two Special Cases of Binary Tree 58
5.4 Properties of Binary Trees 60
5.5 Representation of Binary Tree 61
5.5.1. Linear (Or) Sequential Representation Using Arrays 61
5.5.2. Linked List Representation of Binary Tree Using Pointers 62
5.6 Binary Tree Traversals 64
5.6.1. Preorder Traversal 64
5.6.2. Inorder Traversal 64
5.6.3. Postorder Traversal 64
5.7 Recursive Binary Tree Traversals 65
5.8 Creation of Binary Tree from Its Tree Traversals 66
5.9 Types of Binary Tress 69
5.10 Binary Search Tree 69
UNIT - I
DATA STRUCTURES
1.1 INTRODUCTION TO DATA STRUCTURES:-
1.1.1 Definition:
A data structure is a specialized format for organizing, processing, retrieving and storing data.
(or)
A data structure is a way of organizing and storing data in a computer so that it can be accessed and used efficiently. It refers to the logical or mathematical representation of data, as well as the implementation in a computer program.
(or)
A data structure is a group of data elements that provides the most straightforward way to store and perform various operations on computer data. A data structure is an effective technique to arrange data in a computer.
(or)
In computer terms, a data structure is a Specific way to store and organize data in a computer's memory so that these data can be used efficiently later.
Why should we learn Data Structures?
› Data Structures and Algorithms are two of the key aspects of Computer Science.
› Data Structures allow us to organize and store data, whereas Algorithms allow us to process that data meaningfully.
› Learning Data Structures and Algorithms will help us become better Programmers.
› We will be able to write code that is more effective and reliable.
› We will also be able to solve problems more quickly and efficiently.
1.1.2 Importance of Data Structures:
❖ Efficiency: Data structures are essential for writing efficient code. They help optimize algorithms by providing means to manage large amounts of data efficiently, ensuring operations like insertion, deletion, and searching are performed quickly.
❖ Data Management: They provide a systematic way to organize and manage data. Proper use of data structures ensures data can be accessed and modified effectively.
❖ Reusability: Well-designed data structures can be reused across multiple programs and projects, reducing redundancy and improving maintainability.
❖ Abstraction: They allow for abstraction, which hides the complexities of data management and provides a simpler interface for users to interact with data.
❖ Algorithm Performance: Choosing the right data structure is crucial for the performance of an algorithm. Different algorithms require different data structures for optimal performance.
❖ Memory Management: Efficient data structures help in managing memory allocation and deallocation, preventing memory leaks and enhancing the performance of applications.
❖ Real-world Application: Data structures are the backbone of various real-world applications, from databases and operating systems to networking and artificial intelligence.
1.1.3 Classification of Data Structures:
A data structure provides a structured set of variables that are associated with each other in different ways. It forms a basis of programming tool that represents the relationship between data elements and helps programmers to process the data easily.
Data structure can be classified into two categories:
A. Primitive data structure
B. Non-primitive data structure
Figure 1.1 shows the different classifications of data structures.
Fig.1.1 Classifications of data structures
––––––––
A. Primitive Data Structure
Primitive data structures consist of the numbers and the characters which are built in