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The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called "Divide-and-Conquer"), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.… (mere)
apparently the second most cited computer science book, and for good reason. (no, i don't know the top most cited, and no, its not knuth). but, what a vast and exciting array of pseudocode, algorithms, and their data structures! good largley for being rich and dense, but readable. doesn't waste space over explaining, but should be sufficient for most anyone with a active interest.
an interesting feature, with respect to the exercises and especially problems for each chapter, is that i think cormen subscribes to a methodology where the solution to a problem should often require information or intuition not found in the chapter, nor even necessarily in the preceding chapters. you find yourself driving towards solutions that are used in later sections, or revisiting old problems once you find a better solution later on.
and, of course, cormen is here at dartmouth. one should probably always have a copy handy when writing code. ( )
This book is like an encyclopedia of algorithms. The algorithms are presented with pseudo code so it doesn’t matter what your favorite programming language is. A very rigorous mathematical approach is used for the analysis of for instance performance. ( )
Normally I wouldn't review a textbook, but reading this one is enjoyable.
It's one of the very best textbooks I've ever used. Unbelievably well written. Well organized. Great examples and pictures. Clearly explained proofs. It is easy to read and learn from. I'm surprised I was able to get an already-used copy of this book; I'll be keeping mine for a very long time. ( )
The definitive graduate or upper-level undergraduate computer science textbook. This is the place to go to learn basic algorithms, data structures, proofs of correctness, and big-O notation. I prefer it to Knuth's three-volume opus, because it's shorter and doesn't get bogged down in the details of an artificial assembly language.
Cormen et al. also makes for a fine self-study guide. If you're reading it on your own, check out the MIT Open Course Introduction to Algorithms class, which has a full set of online lectures and problem sets based on this book. ( )
The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called "Divide-and-Conquer"), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.
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knol | Dec 25, 2009 | 
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an interesting feature, with respect to the exercises and especially problems for each chapter, is that i think cormen subscribes to a methodology where the solution to a problem should often require information or intuition not found in the chapter, nor even necessarily in the preceding chapters. you find yourself driving towards solutions that are used in later sections, or revisiting old problems once you find a better solution later on.
and, of course, cormen is here at dartmouth. one should probably always have a copy handy when writing code. (