Algorithm Design and Analysis

📚Algorithm Design and Analysis (2025–2026 Edition) is a complete syllabus-oriented book crafted for BSCS, BSIT, BS Software Engineering students, researchers, software developers, and competitive programmers who aim to master algorithm design, complexity analysis, and optimization techniques.

This edition integrates MCQs, quizzes, and practice problems to help learners strengthen both theoretical understanding and practical application. It covers classical and advanced algorithms, asymptotic notations, recursion, graph theory, dynamic programming, NP-completeness, and approximation techniques with real-world examples.

Students will not only learn to design efficient algorithms but also analyze their correctness, performance, and applicability in diverse computing problems.

📂 Chapters & Topics

🔹 Chapter 1: Introduction to Algorithms

Definition and Characteristics

Importance and Applications

Design Goals: Correctness, Efficiency, Simplicity

Pseudocode Conventions

🔹 Chapter 2: Growth of Functions & Asymptotic Notations

Mathematical Preliminaries

Best, Worst & Average Case Analysis

Big-O, Big-Ω, Big-Θ Notations

Growth Rate Comparisons

🔹 Chapter 3: Recursion and Recurrence Relations

Recursion Basics

Recurrence Solving Techniques

Substitution, Iteration, and Master Theorem

🔹 Chapter 4: Divide-and-Conquer Approach

Strategy and Applications

Binary Search, Merge Sort, Quick Sort

Strassen’s Matrix Multiplication

🔹 Chapter 5: Sorting and Searching Algorithms

Basic, Advanced & Linear-Time Sorting

Binary Search and Variations

🔹 Chapter 6: Advanced Data Structures

BST, AVL, Red-Black Trees, B-Trees

Heaps, Priority Queues, and Hashing

🔹 Chapter 7: Greedy Algorithms

Greedy Methodology

MST (Prim’s & Kruskal’s), Huffman Coding

Activity Selection Problem

🔹 Chapter 8: Dynamic Programming

Overlapping Subproblems & Optimal Substructure

Case Studies: Fibonacci, LCS, Knapsack, OBST

🔹 Chapter 9: Graph Algorithms

Representations: Adjacency List/Matrix

BFS, DFS, Topological Sort, SCCs

🔹 Chapter 10: Shortest Path Algorithms

Dijkstra’s Algorithm

Bellman-Ford

Floyd-Warshall & Johnson’s Algorithm

🔹 Chapter 11: Network Flow and Matching

Flow Networks & Ford-Fulkerson

Maximum Bipartite Matching

🔹 Chapter 12: Disjoint Sets and Union-Find

Union by Rank & Path Compression

Applications in Kruskal’s Algorithm

🔹 Chapter 13: Polynomial and Matrix Calculations

Polynomial Multiplication

Fast Fourier Transform (FFT)

Strassen’s Algorithm Revisited

🔹 Chapter 14: String Matching Algorithms

Naïve, Rabin-Karp, KMP, Boyer-Moore

🔹 Chapter 15: NP-Completeness

NP, NP-Hard & NP-Complete Problems

Reductions & Cook’s Theorem

Example Problems (SAT, 3-SAT, Clique, Vertex Cover)

🔹 Chapter 16: Approximation Algorithms

Approximation Ratios

Vertex Cover, TSP, Set Cover

🌟 Why Choose this Book/app?

✅ Covers complete syllabus of Algorithm Design & Analysis

Includes MCQs, quizzes, and practice problems for mastery

✅ Explains recursion, dynamic programming, greedy & graph algorithms in depth

✅ Bridges theory with real-world problem-solving

✅ Perfect for exam preparation, coding interviews, and competitive programming

✍ This app is inspired by authors:

Thomas H. Cormen, Charles Leiserson, Ronald Rivest, Clifford Stein, Jon Kleinberg, Éva Tardos

📥 Download Now!

Master efficiency, complexity, and optimization with Algorithm Design and Analysis (2025–2026 Edition).