Introduction to Algorithms (MIT Electrical Engineering and Computer Science) [Paperback]

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

Book Description

Series: MIT Electrical Engineering and Computer Science | Publication Date: June 25, 1990

The first edition won the award for Best 1990 Professional and Scholarly Book in Computer Science and Data Processing by the Association of American Publishers. This edition is no longer available. Please see the Second Edition of this title.

Editorial Reviews

Amazon.com Review

If you had to buy just one text on algorithms, Introduction to Algorithms is a magnificent choice. The book begins by considering the mathematical foundations of the analysis of algorithms and maintains this mathematical rigor throughout the work. The tools developed in these opening sections are then applied to sorting, data structures, graphs, and a variety of selected algorithms including computational geometry, string algorithms, parallel models of computation, fast Fourier transforms (FFTs), and more.

This book's strength lies in its encyclopedic range, clear exposition, and powerful analysis. Pseudo-code explanation of the algorithms coupled with proof of their accuracy makes this book is a great resource on the basic tools used to analyze the performance of algorithms. --This text refers to an out of print or unavailable edition of this title.

About the Author

Thomas H. Cormen is Professor of Computer Science and former Director of the Institute for Writing and Rhetoric at Dartmouth College.

Charles E. Leiserson is Professor of Computer Science and Engineering at the Massachusetts Institute of Technology.

Ronald L. Rivest is Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology.

Product Details

• Paperback: 1048 pages
• Publisher: The MIT Press (June 25, 1990)
• Language: English
• ISBN-10: 0262530910
• ISBN-13: 978-0262530910
• Product Dimensions: 9.9 x 8.1 x 1.4 inches
• Shipping Weight: 4.5 pounds
• Average Customer Review: 4.4 out of 5 stars  See all reviews (69 customer reviews)
• Amazon Best Sellers Rank: #730,462 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

45 of 50 people found the following review helpful:

5.0 out of 5 stars The best textbook I have ever seen, January 7, 2000

By 

Ashwin Rao - See all my reviews

This review is from: Introduction to Algorithms (MIT Electrical Engineering and Computer Science) (Hardcover)

I was the instructor for a junior/senior course on Algorithms at the University of Southern California and I used this book as the textbook. Unfortunately, many of the students didn't like this book because they did not appreciate the mathematical flavor of the book. A course on Algorithms is useless without a sound background in discrete mathematics. Hence, this book assumes that you are reasonably strong in Discrete Mathematics.

I haven't seen a better textbook ! Here are some reasons:

1. The discrete mathematics foundations are present in the first few chapters of this book and so, you can quickly brush up on any discrete math background that you may require while using this book.

2. The style of writing is very light and at the same time, rigorous - almost as if you are in the middle of a lecture while reading the book.

3. The material is comprehensive and serves as an excellent reference for other courses and in your future career.

4. The exercises and problems provide a very good learning experience.

5. It's a good-looking book !

59 of 67 people found the following review helpful:

5.0 out of 5 stars A Very Solid Introduction to Algorithms, December 8, 2000

By 

Donovan Rebbechi (Wynnewood, PA United States) - See all my reviews
(REAL NAME)   

This review is from: Introduction to Algorithms (MIT Electrical Engineering and Computer Science) (Hardcover)

It's a good thing that this book has a hard cover (make sure you get the hard cover edition, huh?), because otherwise mine would be in pieces. This book is my favourite book on algorithms. All the others seem somewhat unsatisfactory to me -- they are tied to particular programming languages, they are paperback, and they are for the most part less comprehensive than this book. (except Knuth, which is somewhat more advanced). See the summary of the TOC below for an outline of what the book covers. I guess Sedgewicks new title has been getting better reviews, but it's still not hard cover (-;

This covers a lot of topics, and covers them in some level of mathematical rigor. For example, all assertions about algorithm efficiency are backed up with *proofs*, and key concepts like asymptotics, and big-O notation are covered. To those who think proofs are not essential -- as a mathematician, I'd counter that proofs are absolutely necessary, because you don't know something until you've proven it -- it's easy to make wrong "guesses", or even wrong hand-waving arguments. The examples are all in pseudo-code. Personally, I liked this as it makes implementing the data structures an interesting exercise that forces the reader to think.

The subject matter covered is quite broad, see below. There are some interesting topics that don't get covered (eg AVL trees), but this book does a good job at laying down the foundation.

Some might be intimidated by the theoretical approach, but I for one like it. It's written for computer scientists (or "software engineers"), not get-rich-quick wannabees. This book will force you to think, and if you don't like that, well you can (and should) buy "learn algorithms in 21 seconds" from SAMS or something.

You'll need some background to digest this material. Someone with a year of programming and some discreet math should be ready for it. Note that you won't learn any programming *language* from this book (unless you count pseudo-coed), so you'd better know some before starting !

Summary: PartI: Intro, Growth of functions,Summations, Recurrences, Sets, Counting and Probability

Part II: Heapsort,Quicksort, Sorting in linear time, Medians/order statistics

Part III: Stacks/Queues/Linked lists, Hash tables, Binary search trees, Red-Black trees, Augmented data structures

Part IV: Dynamic programming,Greedy algorithms, Amortized analysis

Part V: B-trees, Binomial heaps, fibonacci heaps, data structures for disjoint sets

Part VI: Elementary graph algorithms, Minimal spanning trees, single-source shortes paths, all pairs shortest paths, maximum flow

Part VII: sorting networks, arithmatic circuits, algorithms for parallel computers, matrix operations, polynomials and fft, number theoretic algorithms, string matching, computational geometry, NP-completeness, Approximation algorithms.

38 of 42 people found the following review helpful:

5.0 out of 5 stars Rigorous coverage of the most widely used algorithms, December 5, 1999

By 

Steven Nicolaou (Boston, MA) - See all my reviews
(REAL NAME)   

This review is from: Introduction to Algorithms (MIT Electrical Engineering and Computer Science) (Hardcover)

I personally bought this book in preparation for the International Olympiad in Informatics (IOI), and it helped me immensely in getting off the ground with the algorithms I had to learn, especially the chapter on Dynamic Programming. Since then, however it has remained a priceless companion during my studies and at home.

This is the definitive reference for algorithms with a firm theoretical and mathematical foundation. Algorithms are treated with a thorough theoretical introduction often with a complete mathematical walkthrough, a clearly thought out solution, a discussion of its pros and cons, lots of clear and consisive diagrams, a pseudocode implementation, and a good deal of serious optimisation discussion. It's written in an accessible manner, starting with the elementary issues, progressing to the advanced and complex thinking needed to conquer them, so you'll find you have to give it your full concentration.

This book will not disappoint. Its explanations are rigorous and its coverage spans all the general purpose algorithms with little focus on their applications but rather on the algorithms themselves. The book covers such major areas as sorting, data structures, advanced design and analysis techniques, graphs, each about a hundred pages on average, and a selection of specialised algorithms such as parallel programming, string matching and computational geometry. Because these algorithms are used everywhere, from games, graphics and simulations to electrical engineering it will have a broad audience and will find a home almost anywhere there is serious programming involved. Each chapter is a unit in itself which means you don't need to read it cover to cover, since they all start off smoothly and handhold you through. Clearly written by professionals, this is the book I know contains the information that I can't find elsewhere.