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Discrete Mathematics

A Comprehensive Guide for BCA & MCA Students

This book is 100% completeLast updated on 2026-06-27

Master Discrete Mathematics — the foundation of Computer Science. Comprehensive guide specially designed for BCA & MCA students with detailed explanations, solved examples, real-world applications, and exam-focused practice. Perfect for university exams, GATE, and interviews.

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About

About the Book

Discrete Mathematics: A Comprehensive Guide for BCA & MCA Students is a complete, student-friendly resource designed to build a strong mathematical foundation for computer science and information technology programs.

Discrete Mathematics forms the essential backbone of computer science. Concepts from this subject are fundamental to understanding algorithms, data structures, databases, cryptography, artificial intelligence, machine learning, and software engineering. This book presents these concepts in a clear, structured, and practical manner specifically aligned with the syllabi of BCA and MCA courses across most Indian universities.

The book covers all major topics with step-by-step explanations, detailed solved examples, real-world applications, and abundant practice exercises. It balances theoretical understanding with problem-solving skills, making it equally useful for university exams, competitive examinations (GATE, UGC-NET), and interviews.

Key Topics Covered:

  • Sets, Relations, and Functions (including advanced concepts like closure, Warshall’s Algorithm, and Hashing Functions)
  • Counting Principles, Permutations, Combinations, and Mathematical Induction
  • Growth of Functions, Asymptotic Notations, and Summation
  • Recurrence Relations with multiple solution techniques (Substitution Method, Recurrence Trees, Master Theorem, Generating Functions)
  • Comprehensive Graph Theory (including Trees, Spanning Trees, Planar Graphs, Graph Coloring, Euler & Hamiltonian Paths)
  • Mathematical Logic — Propositional Logic, Predicate Calculus, Inference Theory, and Logic Gates
  • Lattice Theory, Partial Order Sets, and Hasse Diagrams

Why This Book is Special:

  1. Syllabus-Aligned: Strictly follows the latest BCA and MCA discrete mathematics curriculum.
  2. Beginner to Advanced: Starts with basic concepts and gradually moves to complex topics with clear progression.
  3. Exam-Focused: Large number of solved examples, previous year questions pattern, and practice exercises for strong exam preparation.
  4. Real-World Applications: Every chapter connects mathematical concepts to practical uses in programming, networking, AI, cybersecurity, and data science.
  5. Problem-Solving Emphasis: Develops strong analytical and logical thinking skills required for coding and algorithm design.
  6. Self-Learning Friendly: Clear language, illustrative diagrams, and structured explanations make it ideal for both classroom study and self-study.

This book is more than just a textbook — it is a complete learning companion that helps students not only pass their exams but also build a solid foundation for higher studies and successful careers in the IT industry.

Who Should Read This Book?

  • BCA and MCA students
  • B.Tech / B.E. Computer Science & Engineering students
  • Aspirants preparing for GATE, UGC-NET, and other technical competitive exams
  • Software developers and professionals who want to strengthen their mathematical foundation
  • Researchers and academicians in theoretical computer science

Whether you are encountering Discrete Mathematics for the first time or revising for advanced understanding, this comprehensive guide will help you master the subject with confidence and clarity.


Author

About the Author

Anshuman Mishra

Anshuman Kumar Mishra, M.Tech (Computer Science) Assistant Professor, Doranda College, Ranchi University

Prolific Author of 50+ Books on AI, Machine Learning & Computer Science | 20+ Years Experience

Anshuman Kumar Mishra is a dedicated educator, researcher, and highly prolific author with over 20 years of experience in Computer Science and Information Technology. Holding an M.Tech in Computer Science from BIT Mesra, he brings a rare combination of academic depth and practical teaching expertise.

Currently serving as Assistant Professor at Doranda College under Ranchi University, he has mentored thousands of students, helping them build strong foundations in programming, data science, and artificial intelligence. His student-centric teaching style emphasizes conceptual clarity, hands-on practice, and real-world application.

Anshuman is a prolific author with more than 50 books published across a wide spectrum of computer science and emerging technology domains. From foundational programming languages to advanced topics in Artificial Intelligence, Machine Learning, Reinforcement Learning, Decision Theory, and Computer Vision — his books are widely appreciated by students, educators, and professionals for their clear explanations, strong theoretical foundation, and practical approach.

His extensive body of work reflects his deep commitment to making complex subjects accessible and meaningful for learners at all levels. He is particularly recognized for creating well-structured learning paths that help readers progress from beginner to advanced levels with confidence.

Driven by the mission to democratize quality technical education, Anshuman continues to write and update books that bridge the gap between academic theory and industry practice.

When not teaching or writing, he actively follows and explores new developments in AI, Quantum Machine Learning, and Ethical Intelligence systems.

Contents

Table of Contents

Table of Contents Chapter 1: Fundamentals of Sets and Relations 1-22 1.1 Finite and Infinite Sets 1.2 Uncountable Infinite Sets 1.3 Functions and Relations 1.4 Properties of Binary Relations 1.5 Closure and Partial Ordering Relations Chapter 2: Counting Principles 23-40 2.1 Pigeonhole Principle 2.2 Permutation and Combination 2.3 Principle of Mathematical Induction 2.4 Principle of Inclusion and Exclusion Chapter 3: Growth of Functions and Summation 41-56 3.1 Asymptotic Notations 3.2 Summation Formulas and Properties 3.3 Bounding Summations 3.4 Approximation by Integrals Chapter 4: Recurrence Relations and Their Solutions 57-79 4.1 Recurrence Relations and Their Applications 4.2 Generating Functions 4.3 Linear Recurrence Relations with Constant Coefficients 4.4 Substitution Method 4.5 Recurrence Trees and Master Theorem Chapter 5: Graph Theory Essentials 80-110 5.1 Basic Terminology and Types of Graphs 5.2 Multigraphs and Weighted Graphs 5.3 Graph Representation and Isomorphism 5.4 Connectivity in Graphs 5.5 Euler and Hamiltonian Paths and Circuits 5.6 Planar Graphs and Graph Coloring 5.7 Trees and Their Properties 5.8 Introduction to Spanning Trees Chapter 6: Mathematical Logic and Propositional Logic 111-139 6.1 Logical Connectives 6.2 Well-formed Formulas 6.3 Tautologies and Equivalences 6.4 Inference Theory 6.5 Propositions and Their Logical Operations 6.6 Principle of Duality 6.7 Logic Gates and Their Applications 6.8 Normal Forms in Logic Chapter 7: Predicate Calculus and Rule of Inference 140-158 7.1 Introduction to Predicate Calculus 7.2 Universal and Existential Quantifiers 7.3 Rule of Inference and Their Applications Chapter 8: Relations and Functions 159-201 8.1 Product Sets and Partitions 8.2 Binary Relations and Their Properties 8.3 Domain and Range of Relations 8.4 Matrices of Relations and Digraphs 8.5 Path in Relation and Digraphs 8.6 Boolean Matrices and Adjacency Matrices 8.7 Equivalence Relations and Warshall’s Algorithm 8.8 Functions: Types, Composition, and Inverse 8.9 Hashing Functions and Characteristic Functions 8.10 Permutation Functions Chapter 9: Lattice Theory and Order Relations 202-238 9.1 Partial Order Sets and Hasse Diagrams 9.2 Isomorphism and Duality in Lattices 9.3 Product of Two Sets 9.4 Lattice as a Partially Ordered Set 9.5 Lattices as Algebraic Systems 9.6 Complete and Bounded Lattices 9.7 Sub-Lattices and Their Properties

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