- Series: MIT Press
- Hardcover: 1312 pages
- Publisher: The MIT Press; 3rd edition (July 31, 2009)
- Language: English
- ISBN-10: 0262033844
- ISBN-13: 978-0262033848
- Product Dimensions: 8 x 1.8 x 9 inches
- Shipping Weight: 4.7 pounds (View shipping rates and policies)
- Average Customer Review: 4.3 out of 5 stars See all reviews (447 customer reviews)
- Amazon Best Sellers Rank: #2,850 in Books (See Top 100 in Books)
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Introduction to Algorithms, 3rd Edition (MIT Press) 3rd Edition
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As an educator and researcher in the field of algorithms for over two decades, I can unequivocally say that the Cormen et al book is the best textbook that I have ever seen on this subject. It offers an incisive, encyclopedic, and modern treatment of algorithms, and our department will continue to use it for teaching at both the graduate and undergraduate levels, as well as a reliable research reference.(Gabriel Robins, Department of Computer Science, University of Virginia)
Introduction to Algorithms, the 'bible' of the field, is a comprehensive textbook covering the full spectrum of modern algorithms: from the fastest algorithms and data structures to polynomial-time algorithms for seemingly intractable problems, from classical algorithms in graph theory to special algorithms for string matching, computational geometry, and number theory. The revised third edition notably adds a chapter on van Emde Boas trees, one of the most useful data structures, and on multithreaded algorithms, a topic of increasing importance.(Daniel Spielman, Department of Computer Science, Yale University)
About the Author
Thomas Cormen is Professor of Computer Science at Dartmouth College. Charles Leiserson is Professor of Computer Science and Engineering at MIT. Ronald L. Rivest is Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT. Clifford Stein is Professor of Industrial Engineering and Operations Research at Columbia University.
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Top Customer Reviews
This book is impressive! It covers a lot of subject matter and is clearly worded. However, you're going to get lost because this often reads more like a reference manual than a conversation that appeals to intuition. You'll be pushed into analyzing algorithms for theoretical data structures that you fuzzily remember (if at all). But, nonetheless, throw enough man hours into this book and you will learn concrete approaches to determining just how hard you're making the computer work.
My biggest criticism is that, as an *introduction*, this book doesn't do the best job at warming up readers to new tools and methodologies. This is an 'eh, just push them into the deep end' kind of approach to learning.
I recall struggling with the subject matter, despite having worked with computers since childhood and completing the requisite high-school mathematics courses. The approach taken by the authors is fairly direct; there is little hand-holding, although there are 100 pages of appendices covering pre-requisites.
I had my moments of wanting to hurl it across the room, but it remained amongst the few texts I held onto, thinking it might be useful or enlightening in the future, relative to the burden of lugging it around. I've since upgraded from the 2nd edition to the 3rd, and occasionally pick it up, read a few sections or a chapter and complete some exercises.
Each topic in the book is covered in the same way:
- Explanation of problem or concept.
- Example(s) and/or diagram(s)
- Mathematical proofs, where applicable.
- Problem set
Tip: Concrete Mathematics by Knuth is good primer, establishing the specific discrete and continuous mathematical techniques underpinning the algorithms, and filling several knowledge gaps. Also, Cormen has published a more approachable version of this text ("Algorithms Unlocked") which which be more appropriate to some.
None of the solutions to the exercises are provided in the book, but a few are available at the books website: mitpress.mit.edu/books/introduction-algorithms.
Great reference and great read when you need to get out of the box and think creatively.
For a more approachable intro to algorithms, check out Sedgewick's book. That book also has a companion website and Coursera course. it's hard to go wrong with that combo.
As such it probably earns more than the 3 stars I will give it from my own perspective. My reasons for this are inherent in my own relationship to the topic - as a "user" if you will.
I bought this book in order to dig deeper into my own conceptual understanding of algorithms, working by my myself.
For this purpose I found the book to be quite tedious. Disadvantageous are especially the fetishization of compact representations, a tendency mathematicians are known to have.
It really doesn't pull a lot of punches when it comes to dishing out mathematical expressions for the reader to patiently unfold for themselves in order to really grasp the meaning of the surrounding text - Ingestion of the material can become a true test of perseverance this way.
It also needs to be said that this is one of these books that bears "Introduction" in the title when it works in fact more like an encyclopedic heavyweight 1200 page quasi-complete survey of the field.
I'm writing this so you know what you are getting into. Be sure this is what you're looking for and what you need.
My only complaint is that the binding has completely stated disintegrating after only 9 weeks of use. All of chapters 15 and 16 are completely falling out of my copy (and this is getting worse). Very disappointing as I plan on using it for a long time.