Algorithms for Competitive Programming

Core algorithms for contest-style problem solving

Algorithms for Competitive Programming brings together the techniques that show up again and again in programming contests, coding interviews, and online judges. The book is organized as a practical tour through the fundamentals, with chapters that move from recursion and complexity analysis into data structures, sorting, divide and conquer, dynamic programming, graph theory, geometry, number theory, combinatorics, and string manipulation.

The structure makes its purpose very clear: this is a hands-on reference for solving problems efficiently, not a theoretical survey. The contents include chapter notes, exercises, solutions, and additional problem sets, giving readers plenty of room to practice the ideas as they go. For anyone building speed and confidence with algorithmic problem solving, that mix of explanation and application is especially useful.

What the book covers

• Fundamental techniques such as recursion, memoization, asymptotic analysis, and bitwise operations
• Core data structures including trees, heaps, sets, maps, segment trees, and binary indexed trees
• Classic algorithms for sorting, searching, dynamic programming, shortest paths, spanning trees, matching, and flows
• Geometry and number theory topics that frequently appear in advanced problem sets
• String algorithms such as KMP and Manacher’s algorithm

Built for practice

The chapter-by-chapter exercise sections and solutions make the book especially useful for self-study. Readers who like to learn by working through examples will appreciate the way it pairs explanations with problem sets and follow-up answers. It is a strong fit for students, competitive programmers, and interview preparation alike.

A focused reference for technical readers

If you want a compact roadmap to the algorithms most often used in competitive programming, this title offers a clear and practical path through the subject. It is especially suited to readers who want structured coverage of the core toolkit and a book they can return to when a problem calls for the right method, not just the fastest guess.