Author : Tithirupa Tapaswini, Dharmendra Gupta, Kailash Kumar Baraskar, Atharv Parsai

ISBN : 978-93-48717-18-4

This comprehensive and accessible guide is crafted for students, educators, and professionals who seek a deep understanding of how algorithms are developed, analyzed, and optimized to solve real-world problems efficiently.

This book covers a broad spectrum of topics, including:

• Core algorithmic paradigms: Divide and conquer, greedy algorithms, dynamic programming, backtracking, and branch & bound
• Algorithm complexity analysis: Time and space complexity, asymptotic notations, and recurrence relations
• Sorting, searching, and selection algorithms
• Graph algorithms: BFS, DFS, shortest paths, spanning trees, and network flows
• Advanced topics: NP-completeness, approximation algorithms, randomized algorithms, and amortized analysis
• Case studies and real-world applications in scheduling, optimization, and computational geometry

With a balance of theoretical rigor and hands-on problem solving, each chapter includes clear explanations, annotated pseudocode, step-by-step examples, and a rich collection of exercises and challenges.

Whether you're preparing for competitive programming, acing technical interviews, or excelling in academic coursework, this book will sharpen your algorithmic skills and foster a mindset geared toward efficient problem-solving.