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Introduction to Algorithms, 3rd Edition (Mit Press) 3rd Edition

by Thomas H Cormen (Author), Charles E Leiserson (Author), Ronald L Rivest (Author),
4.6 4.6 out of 5 stars 2,188 ratings
#1 Best Seller in Data Structure and Algorithms
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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.

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  1. ISBN-10
    9780262033848
  2. ISBN-13
    978-0262033848
  3. Edition
    3rd
  4. Publisher
    MIT Press
  5. Publication date
    September 1, 2009
  6. Language
    English
  7. Dimensions
    9.08 x 8.18 x 2.06 inches
  8. Print length
    1292 pages
  9. See all details
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Editorial Reviews

Review

""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

"As an educator and researcher in the field of algorithms for over two decades, I can unequivocally say that the Cormen 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

"In light of the explosive growth in the amount of data and the diversity of computing applications, efficient algorithms are needed now more than ever. This beautifully written, thoughtfully organized book is the definitive introductory book on the design and analysis of algorithms. The first half offers an effective method to teach and study algorithms; the second half then engages more advanced readers and curious students with compelling material on both the possibilities and the challenges in this fascinating field."--Shang-Hua Teng, University of Southern California

"

About the Author

Thomas H. Cormen is Professor of Computer Science and former Director of the Institute for Writing and Rhetoric at Dartmouth College. He is the coauthor (with Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein) of the leading textbook on computer algorithms, Introduction to Algorithms (third edition, MIT Press, 2009).

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.

Clifford Stein is Professor of Industrial Engineering and Operations Research at Columbia University.

Product details

  • ASIN ‏ : ‎ 0262033844
  • Publisher ‏ : ‎ MIT Press; 3rd edition (September 1, 2009)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 1292 pages
  • ISBN-10 ‏ : ‎ 9780262033848
  • ISBN-13 ‏ : ‎ 978-0262033848
  • Reading age ‏ : ‎ 18 years and up
  • Grade level ‏ : ‎ 12 and up
  • Item Weight ‏ : ‎ 4.95 pounds
  • Dimensions ‏ : ‎ 9.08 x 8.18 x 2.06 inches
  • Customer Reviews:
    4.6 4.6 out of 5 stars 2,188 ratings

About the authors

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  1. Thomas H. Cormen

    Thomas H. Cormen

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    Thomas H. Cormen is Emeritus Professor and former Chair of the Dartmouth College Department of Computer Science and former director of the Dartmouth College Institute for Writing and Rhetoric. He received the B.S.E. degree in Electrical Engineering and Computer Science from Princeton University in 1978 and the S.M. and Ph.D. degrees in Electrical Engineering and Computer Science from MIT in 1986 and 1993, respectively. He is coauthor of the leading textbook on computer algorithms, Introduction to Algorithms, which he wrote with Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. The book, now in its fourth edition, has been translated into several languages. He is also the author of Algorithms Unlocked, a gentle introduction to understanding computer algorithms and how they relate to real-world problems.

    Since retiring from Dartmouth, Cormen serves in the New Hampshire House of Representatives, representing the city of Lebanon, New Hampshire. He serves on the Science, Technology and Energy Committee.

    In his spare time, Cormen likes skating (inline and nordic), paddling, and cooking and eating barbecue. He considers himself the world's worst electrician who has a Ph.D. in electrical engineering.

    See more on the author's page
  2. Clifford Stein

    Clifford Stein

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    Clifford Seth Stein (born December 14, 1965), a computer scientist, is a professor of industrial engineering and operations research at Columbia University in New York, NY, where he also holds an appointment in the Department of Computer Science. Stein is chair of the Industrial Engineering and Operations Research Department at Columbia University. Prior to joining Columbia, Stein was a professor at Dartmouth College in New Hampshire.

    Stein's research interests include the design and analysis of algorithms, combinatorial optimization, operations research, network algorithms, scheduling, algorithm engineering and computational biology.

    Stein has published many influential papers in the leading conferences and journals in his fields of research, and has occupied a variety of editorial positions including in the journals ACM Transactions on Algorithms, Mathematical Programming, Journal of Algorithms, SIAM Journal on Discrete Mathematics and Operations Research Letters. His work has been funded by the National Science Foundation and the Sloan Foundation. As of November 1, 2015, his publications have been cited over 46,000 times, and he has an h-index of 42.

    Stein is the winner of several prestigious awards including an NSF Career Award, an Alfred Sloan Research Fellowship and the Karen Wetterhahn Award for Distinguished Creative or Scholarly Achievement. He is also the co-author of two textbooks:

    Introduction to Algorithms, with T. Cormen, C. Leiserson and R. Rivest, which is currently the best-selling textbook in algorithms and has been translated into 8 languages. About 39,500 of Stein's 46,000 citations are made to this book.

    Discrete Math for Computer Science, with Ken Bogart and Scot Drysdale, which is a new textbook that covers discrete math at an undergraduate level.

    Stein earned his B.S.E. from Princeton University in 1987, a Master of Science from The Massachusetts Institute of Technology in 1989, and a PhD also from the Massachusetts Institute of Technology in 1992.

    In recent years, Stein has built up close ties with the Norwegian research community which earned him an honorary doctorate from the University of Oslo (May 2010).

    Bio from Wikipedia, the free encyclopedia. Photo by Sergio01 (Own work) [CC BY-SA 3.0 (http://creativecommons.org/licenses/by-sa/3.0) or GFDL (http://www.gnu.org/copyleft/fdl.html)], via Wikimedia Commons.

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  3. Charles E. Leiserson

    Charles E. Leiserson

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

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  4. Ronald L. Rivest

    Ronald L. Rivest

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    Ronald Linn Rivest (/rɪˈvɛst/; born May 6, 1947) is a cryptographer and an Institute Professor at MIT. He is a member of MIT's Department of Electrical Engineering and Computer Science (EECS) and a member of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). He was a member of the Election Assistance Commission's Technical Guidelines Development Committee, tasked with assisting the EAC in drafting the Voluntary Voting System Guidelines.

    Rivest is one of the inventors of the RSA algorithm (along with Adi Shamir and Len Adleman). He is the inventor of the symmetric key encryption algorithms RC2, RC4, RC5, and co-inventor of RC6. The "RC" stands for "Rivest Cipher", or alternatively, "Ron's Code". (RC3 was broken at RSA Security during development; similarly, RC1 was never published.) He also authored the MD2, MD4, MD5 and MD6 cry.ptographic hash functions. In 2006, he published his invention of the ThreeBallot voting system, a voting system that incorporates the ability for the voter to discern that their vote was counted while still protecting their voter privacy. Most importantly, this system does not rely on cryptography at all. Stating "Our democracy is too important," he simultaneously placed ThreeBallot in the public domain.

    Bio from Wikipedia, the free encyclopedia. Photo by Ronald L. Rivest (Own work) [CC BY-SA 4.0 (http://creativecommons.org/licenses/by-sa/4.0)], via Wikimedia Commons.

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Customer reviews

4.6 out of 5 stars
4.6 out of 5
2,188 global ratings
Top-Notch Content, Poor Binding
4 Stars
Top-Notch Content, Poor Binding
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.
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Top reviews from the United States

Kindle Customer
5.0 out of 5 stars Excellent Introduction to CS for math majors
Reviewed in the United States on April 23, 2014
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I am a math major who has taken a few cs courses from the cs department at my university. Up until reading this book cs has always been a bit of a mystery to me. I have heard a million and one time how cs is based on mathematics but aside from understanding the idea of traversing through arrays as you would the indexes of a sequence, I have never really seen the connection between the two subjects. This book does an amazing job of demonstrating the mathematical basis of cs. From the very beginning when the authors deconstruct the for-loop used in a insert-sort into a variation on mathematical induction the lines between the two subjects are made crystal clear.

I would agree that a pretty solid understanding of mathematics is required for this book, and I can see why someone coming from a typical undergraduate education in cs would find it difficult and intimidating to tackle this book. It definitely does not teach you how to program or the basics of object oriented design as it proceeds to teach you about structure and design of algorithms. I can also understand why someone hoping to simply get a job as a "programmer" or "software engineer" would not necessarily be well served by this book. The authors are very upfront on this note though, and specifically warn prospective students that they are not going to teach them how to "code" solutions to common cs problems. What they are going to teach them is the fundamentals of algorithm analysis and design. How valuable prospective students find this approach is going to depend entirely on what exactly they hope to do with their understanding of computer science. If you want to learn how to code and be paid to be a developer (not a bad line of work by any stretch of the imagination) you might want to look else where.

For someone coming from a mathematics background though (whether it's an applied field such as statistics or numerical analysis or a pure field like abstract algebra or analysis) this is an excellent introduction to the field of computer science. If you are coming from a math background the analysis and structure of algorithms as presented in this book will instantly click. For me personally I loved the fact that the underlining mathematical basis of cs did not get lost in details of coding or working within certain developmental environments like Eclipse. Again, probably not an ideal choice for someone looking to learn this particular subjects, but definitely a good choice for math majors (or prospective cs grad students).
27 people found this helpful
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5.0 out of 5 stars Great condition
Reviewed in the United States on April 25, 2024
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What you see is what you get.
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RS
5.0 out of 5 stars Flawless Condition
Reviewed in the United States on April 13, 2024
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Book arrived early and was in pristine condition.
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bed-rock_support
5.0 out of 5 stars "An Introduction to Algorithms" is solidly worthwhile.
Reviewed in the United States on September 16, 2012
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"An Introduction to Algorithms", a big book, is worthwhile the time. But, I must admit to being 1/4 through iTunes U MIT course "6-046J: Introduction to Algorithms". The textbook feedback is seriously helpful, but I could not manage without the lectures. For what it is worth, my life's course has been the trash-heap quality programming must immediately face, and I've started the course to try to put into some perspective what my efforts have meant over the years, if now largely obsolete. The number of relevant insights have been affirming- I've played in a busy patch and many of the topics covered (to date) have indeed been of real interest ... if only I had known a bit more at the time about what was in fact a lot of blundering around. And, there are some gems. My 1968 Graduate Diploma included some list management, for which which "move to front- MTF" can only be described as spookily revealing of what was going on all those years ago. Modern methods are scary. Such a simple process being within 50% of the efficiency (25% as described in the applicable lecture with reference to the optimising original paper) of what God could manage is humblingly inspiring. Buy the book if you intend to devote a slab of life to getting better acquainted with modern applied logic, but remember the lectures.
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J. Bodah
4.0 out of 5 stars Very enjoyable, but confusing at times
Reviewed in the United States on May 5, 2011
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Algorithms is the type of subject that can make you put your hand on your head in frustration due to the technical nature of the subject. This book does a terrific job of demystifying topics and giving you a clear and concise notion of the fundamentals which make the algorithm work. In turn, the authors have gotten me to love learning about algorithms. Every chapter is a new challenge, and the authors are there to help guide you the whole way.

Cormen's Algorithms book is highly regarded as one of the best algorithms book out there, and though I have no experience with any other algorithms texts, it's fairly obvious to me now why that is true. Cormen's book is mostly well-organized, is easily readable (especially with all the great pictures and examples!), and is best used as a workbook text. Pretty much all of the chapters rely on chapters previous to some degree, and the exercises especially reflect this behavior as many of them require you to you optimization learned in previous chapters to modify current algorithms. Overall, I have very few complaints, and this text has been one of my favorites throughout college.

My first complaint is that the text begins by throwing you in to the analysis of insertion sort before defining any notation or mathematics used to analyze the algorithm. While I understand that the idea is to introduce you to what algorithm analysis really is, the chapter felt more confusing than helpful. I would much rather the book started with background information first.

Secondly, the mathematical chapters are very brief and vague. Chapters 4 and 5 are particularly bad due to the lack of depth, explanation, and clarity. The examples are far from satisfactory, particularly those regarding probability and recurrences. While these chapters had excellent problem sets, I needed an external source to help me deal with cases not covered in the text. One example of a topic I had trouble with was solving for the number of levels a recurrence tree has. The book only presents trivial examples of this while the problem sets ask for significantly more work. One or two worked out examples, even if they were only included in the selected answers, would have been very helpful.

The last issue that I had with the book was the lack of explanation given in the analysis of specific algorithms. For example, the runtime analysis of Kruskal's minimum spanning tree algorithm felt far from intuitive. The author does not take enough time to explain where some analysis techniques came from and why they were used. Though many of the algorithms are discussed in enough detail, there are several more advanced algorithms which feel like they were thrown into the text without enough care.

Despite all these issues I've been very pleased with my purchase and the time I've invested in it. I would recommend the book to anyone with interest in algorithms. While some knowledge of basic mathematical analysis and probability theory would be helpful, it's pretty easy to get by without either of these. Though the explanation of some of the more technical parts of the book is lacking, the authors do a great job of translating complicated psuedo-code and notational necessities into something which is very easy to understand
15 people found this helpful
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Francisco
5.0 out of 5 stars para los ingenieros
Reviewed in Mexico on June 19, 2022
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si eres ingeniro de software o ingeniero informatico en general, este libro es indispensable, no es un libro de solo leer y de que en un mes lo terminas, hay que leerlo, entenderlo, y trabajar los ejercicios, si quieres aplicar para alguna posicion en una FAANG el 90% de las pruebas tecnicas estan basadas en cosas de este libro, por lo que dominarlo, te deja casi seguro que pasaras las entrevistas :)
5 people found this helpful
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Dina
5.0 out of 5 stars nice book
Reviewed in Canada on March 17, 2022
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Excellent book. Got the book as used but it appears to be new. Very happy with the purchase.
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Luis Carlos Absalon Rojas Torres
5.0 out of 5 stars Nao é por acaso que é a Biblia dos Algoritmos neh
Reviewed in Brazil on December 13, 2021
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Gostei da qualidade do livro. Ja tinha o pdf porém este livro é daqueles que vc quer na sua biblioteca
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Ajit kumar yadav
5.0 out of 5 stars Good quality
Reviewed in India on May 4, 2024
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The quality of book is good. Delivery time could be improved.
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Valentino Tomasovic
5.0 out of 5 stars Sorgfältig
Reviewed in Germany on May 19, 2023
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Das Produkt kam sorgfältig und gut verpackt an. Es weist leichte Gebrauchsspuren auf, was aber beim Kauf mit angegeben wurde. Somit passt alles und ich bin zufrieden.
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