Algorithms Illuminated
Omnibus Edition

‘In my experience, students find Algorithms Illuminated much more relatable and motivating to read than other algorithms books. The presentation style is very modern and honest: complicated ideas are broken into digestible chunks with the explicit recognition that the reader is indeed facing deep content; pseudocode, proofs, and mathematical techniques are presented truthfully without hiding "technical/boring" details; and every problem is well-motivated with the actual reasons that computer scientists care about it. The reader gets the feeling that the book is talking directly to them and inviting them to be part of the story, not just a guest who looks at the highlights and moves on.' Saray Shai, Wesleyan College

‘This fabulous book is an ideal introduction to the design and analysis of algorithms. Algorithms Illuminated stands out for its accessible and readable style, with plenty of examples, quizzes and problems for students to check their understanding. The clarity of the exposition brings out the beautiful ideas at the core of the subject. I highly recommend Algorithms Illuminated to anyone starting out with algorithms!' Mary Wootters, Stanford University

‘Tim Roughgarden's Algorithms Illuminated is a well-crafted, thorough, and engaging presentation of algorithms on a wide range of topics. The chapters on NP-hard problems are particularly remarkable, as they overturn the conventional wisdom that this topic is too hard for students to understand. I have found that my students really benefit from this approach and strongly recommend these books to others.' Avraham Leff, Yeshiva College

‘Look through the Table of Contents and you might conclude that this is just another algorithms book. Don't be fooled. What makes this book special – what makes this book the first of its kind – is Tim Roughgarden's singular ability to weave algorithm design with pedagogical design. Learners need opportunities to check their understanding at key points, to study examples, to see algorithms in contexts that they care about, to confront the needed mathematical background buffered by these motivating contexts. It's all here, carried along by Roughgarden's enthusiasm not only for algorithms but also for the people who want to learn them.' Daniel Zingaro, University of Toronto