Algorithms
This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and ea…
This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and ea…
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Algorithms by Sanjoy Dasgupta, Christos Papadimitriou, and Umesh Vazirani is a comprehensive undergraduate textbook developed from extensive class-testing at UC Berkeley and UC San Diego. The book explains fundamental algorithm design in a narrative style that makes complex material enjoyable and easy to digest. It focuses on the crisp mathematical ideas behind each algorithm, presenting them intuitively and rigorously without excessive formalism. Special boxes provide historical context, practical applications, and mathematical excursions. The text covers core topics like sorting, graphs, dynamic programming, and NP-completeness, with carefully chosen advanced topics that can be skipped in a one-semester course. It includes an accessible treatment of linear programming and an optional chapter on quantum factoring. A solutions manual is available, making it a complete learning package for students and instructors.
This book is ideal for undergraduate computer science students taking a first course in algorithms, as well as instructors seeking a well-structured, class-tested textbook. It suits self-learners with basic programming and discrete math background who want an intuitive yet rigorous introduction. Advanced students will appreciate the optional chapters on linear programming and quantum algorithms. Professionals needing a refresher on algorithmic fundamentals will also benefit from the clear explanations and historical insights.
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