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Introduction to Algorithms, Third Edition [Hardcover] Hardcover – July 31, 2008


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Product Details

  • Hardcover
  • Publisher: The MIT Press; third edition edition (July 31, 2008)
  • ASIN: B0041E5P74
  • Average Customer Review: 4.3 out of 5 stars  See all reviews (174 customer reviews)
  • Amazon Best Sellers Rank: #11,352,338 in Books (See Top 100 in Books)

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Customer Reviews

The book is very clear and precise .
Kai Sum Li
In fact, this book is really aimed at graduate computer science students and is often on the reading list of Ph.
calvinnme
Studying this book will help you land a job faster and for better pay.
Jon Shemitz

Most Helpful Customer Reviews

581 of 603 people found the following review helpful By M. Leeper on December 5, 2009
Format: Hardcover
First of all, this is the quintessential book on algorithms. If you want to learn, this is the book to get. The information in the book is awesome and it can make an excellent reference.

Students will need a very strong mathematical background and a strong arm to even think about picking up this book because the it is heavy (both physically and metaphorically). Mastery of discrete math is a must, graph theory, programming, and, combinatorics will also help.

With that said, this book falls short in one MAJOR area, explanations. Too often explanations are left out and left as exercises and there are no solutions to the exercises! Or details are replaced by ambiguous statements such as of "cleary, this works", or "it is easy to see that this ...". I get the concept of learning by doing, really I do, but there should be some kind of solutions so the student can CHECK his/her understanding of the material and sometimes the exercises are not about advanced aspects of a concept, sometimes it is the core material. Even if the solution manual only contained a simple answer without the work. Not only would it help tremendously but the purpose of doing the exercises would be preserved; that is the student getting his/her "hands dirty" and working out a problem.

For the love everything good and pure in this universe, I really wish writers of mathematical books would stop using statements like "clearly this works" or "it is easy to see", "it is obvious" etc. While that may be true for you and your brilliant circle of colleagues, everything is not always clear and obvious to your readers. Save all of that ambiguity for your research paper.

A great book should deliver in two areas; it should challenge and it should inform. The challenge is there, no doubt.
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182 of 194 people found the following review helpful By Clinton Staley on August 29, 2011
Format: Hardcover
I'm a professor of Computer Science at a respected teaching university, and have been the principal instructor of our introductory algorithms class for the past several years. I used Cormen (doesn't *everyone*?) for a year or two, but have finally relegated it to recommended-text status.

On the plus side, the text is, as my review title says, magisterial. It covers the field comprehensively and authoritatively. When one of the authors is the "R" in RSA, and others are well-known names, you can count on the text's expertise and accuracy. I've never found an error in this text.

BUT.... The pedagogy needs work. Explanations tend to jump too quickly to pure mathematical notation, and there are often insufficient concrete examples. The pseudocode has one-letter variable names that appear at times to be randomly generated :). At least the latest edition fixes what was a baffling indentation style. If you took a sample of 100 CS undergrads and asked them to learn algorithms principally from this text, I'd venture a guess that only the 10 brightest could do so. And even they'd be baffled at times.

I apologize for having to offer such an "emperor is naked" review to such a highly respected work, but it's time to consider more carefully pedagogical texts in the undergrad market.
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141 of 159 people found the following review helpful By calvinnme HALL OF FAMETOP 1000 REVIEWERVINE VOICE on November 7, 2009
Format: Hardcover
An algorithm is nothing more than a set of computational steps that transform a specific input into a desired output. From that definition, there are plenty of books on the market that are "cookbooks" of algorithms and will enable you to do just that - transform specific inputs into outputs, complete with source code, and with no real depth of understanding of your own required. However, to be a computer scientist versus a programmer, you need to know what makes an efficient algorithm, why is a particular algorithm efficient, what kinds of common data structures are involved in various computing problems, how to traverse those data structures efficiently, and a notation for analyzing various algorithms. This book will help you learn all of that. The study of the theory of algorithms is not to be undertaken lightly, and I don't recommend you attempt to self-study such a complex subject with such strong mathematical underpinnings. In fact, this book is really aimed at graduate computer science students and is often on the reading list of Ph.D. qualifying examinations in that field.

For students of graph theory, you might find your knowledge solidly supplemented by the material in chapters 22 through 26 on graph algorithms. The last section of the book, "Selected Topics", goes over various specific algorithms from many fields using the knowledge of algorithm design and analysis you have learned up to this point in the book. Throughout, the text is very clear, and there are plenty of instructive diagrams and pseudocode.

One of the most interesting parts of the book is the chapter on NP-completeness. This is the study of problems for which no efficient algorithm has ever been found. These problems are interesting for two reasons.
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55 of 62 people found the following review helpful By Emre Sermutlu on December 6, 2009
Format: Hardcover Verified Purchase
I have studied algorithms using several books, and this is by far the best. It is comprehensive (twice as thick as the average book), you can find everything you are looking for. It is pedagogical too, always starts with simpler problems. I have also used the first edition for some time, and can say that this one is much improved as a result of feedback from instructors and students. Everything from pseudocode to page layout has been touched in some way, and made easier to read and understand for the student.

The only negative thing about this book is the lack of solutions to exercises. The authors must have realized the importance of this. They published a small subset of solutions on the web, but that is inadequate.
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