Introduction to Algorithms (The MIT Press) 3rd Edition, Kindle Edition

by Thomas H. Cormen (Author), Charles E. Leiserson (Author), Ronald L. Rivest (Author),

575 customer reviews

ISBN-13: 978-0262033848

ISBN-10: 0262033844

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A new 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 new 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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File Size: 23481 KB
Print Length: 1312 pages
Publisher: The MIT Press; 3 edition (July 31, 2009)
Publication Date: July 31, 2009
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B007CNRCAO
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gripper

Somewhat strenuous as a text book to self-learn algorithms from

August 19, 2016

Verified Purchase

An impressive volume that covers many many algorithmic strategies and is surely a major achievement in completeness and accuracy, and should also be pretty unique in its range from mathematical representations to concrete pseudo-code for algorithm implementation. Certainly a book to admire, featuring some excellent buildups and explanation paths. I imagine it to be highly esteemed as reference for undergraduate year-long series of lectures on algorithms in a university setting.

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.

43 people found this helpful

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Matthew

Good, But Still Very Complex!

March 20, 2016

Format: HardcoverVerified Purchase

For background, I am a not-so-sharp CS undergrad that used this book for an intro. to algorithms class. I've done linear algebra, struggled my way through a "calculus" probability course, and enjoyed implementing many typical data structures. My learning style relies on simple examples (especially visual) accompanied by a concise explanation. Here are my thoughts:

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.

44 people found this helpful

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Ben Bitdiddle

Text is pretty good but has pedagogical weaknesses

October 6, 2016

Format: HardcoverVerified Purchase

I think this is a pretty good book that is easy to read if you have a strong background in proof-based math.

Highlights:
- The introduction (Chapters 1-4) is really good and does a good job setting up all the fundamental concepts of algorithms. I think a lot of people tend to skip over introductions because they think they know all of it already, but this is an introduction that I recommend reading the whole way through.
- The book is a pretty light read (none of the math is too difficult) and each chapter is a good length.
- I think the material on dynamic programming and greedy algorithms was particularly enlightening, and if you read it the whole way through you actually learn how to prove that greedy algorithms work, instead of just being like "let's use a greedy algorithm because it seems right"
- I was able to copy a lot of CLRS code almost verbatim in my programming interviews and pass them.
- The figures are really well done and informative.

Drawbacks:
- The pseudocode has a lot of one-letter variable names, and while this follows the tradition of pure math, it also makes understanding the algorithms more difficult than it should be.
- Sometimes the pseudocode is not the "easiest" possible pseudocode (for example, merge sort), and I think it would be better if the authors presented a simpler version of the pseudocode first and then extended it to the optimal version. But then I guess CLRS would be even longer than it already is.
- The arrays are 1-indexed, which makes it trickier to convert to code. Also there are some sections of the textbook (the counting sort section) where some of the arrays are 0-indexed and other arrays are 1-indexed, which is just weird.
- I think the material on graphs, particularly the derivations, could be done in a more engaging and intuitive way. The derivations in Chapters 22-24 were a long series of small uninteresting lemmas, instead of a small number of harder, more insightful theorems. I found derivations elsewhere on the internet that were a lot more interesting and built more intuition about why the procedures worked. I feel like the rest of the book is pretty good though, so maybe all the graph stuff was written by a separate person who is not very good at explaining things.

12 people found this helpful

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Top-Notch Content, Poor Binding

June 3, 2016

Format: HardcoverVerified Purchase

This is probably the most well known and most used textbook on the subject, and with good reason. An excellent resource, covering just about everything you need to know for a good understanding of Algorithms. (side tip, my friends in the industry call this the "How To Pass a Google Interview" book).

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.

8 people found this helpful

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Monday Monkey

Thorough, Rigorous, Maybe not Best for Most Beginners

October 31, 2015

Format: HardcoverVerified Purchase

I'm reviewing this for what it is: An academic text that also serves as a collective document of algorithms for the community (computer science, etc.). This is not a beginner text. It's a first-class algorithms book that is very academically rigorous. That's not a put-down.

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.

6 people found this helpful

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October 1, 2015

Format: PaperbackVerified Purchase

The printing is not clear.

13 people found this helpful

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Most recent customer reviews

The physical book is gorgeous.

Published 17 days ago

Tyler

Poorly written

This book covers many important topics, but it is poorly written. The main ideas are hard to find, and there are many verbose examples with unclear motivation.Read more

Published 23 days ago

Nate

Academic and not practical

It's an academic's textbook. If you are a software engineer preparing for a software engineering interview you shouldn't read this book.Read more

Published 28 days ago

Ashley Maynez

No complaints. Trusted seller.

Good condition for a good price. Can’t complain.

Published 1 month ago

Myszka_Miki

Classic computer science book

This is the Indian edition and is quite of a bargain, as it is way cheaper than the US edition. The only problem I have with it is the paper quality: the pages have some purple...Read more

Published 1 month ago

Tuan Tiep

Five Stars

excellent book

Published 2 months ago

Andrew

Five Stars

Extremely useful as both a student and going forward as a programmer.

Published 2 months ago

lily

Four Stars

Pretty inornate, but easy to understand and covers two semesters of algorithmic analysis curriculum.

Published 2 months ago

Dae Hyun Kim

Five Stars

Good

Published 3 months ago

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