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Introduction to Algorithms [Paperback]

Thomas H Cormen
4.3 out of 5 stars  See all reviews (6 customer reviews)

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Book Description

10 Aug 2001 0262531968 978-0262531962 2nd Revised edition
This title 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. This second edition features new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming, as well as extensive revisions to virtually every section of the book. In a subtle but important change, loop invariants are introduced early and used throughout the text to prove algorithm correctness. Without changing the mathematical and analytic focus, the authors have moved much of the mathematical foundations material from Part I to an appendix and have included additional motivational material at the beginning.


Product details

  • Paperback: 1202 pages
  • Publisher: MIT Press; 2nd Revised edition edition (10 Aug 2001)
  • Language: English
  • ISBN-10: 0262531968
  • ISBN-13: 978-0262531962
  • Product Dimensions: 23 x 20.4 x 5 cm
  • Average Customer Review: 4.3 out of 5 stars  See all reviews (6 customer reviews)
  • Amazon Bestsellers Rank: 256,352 in Books (See Top 100 in Books)

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Amazon Review

Aimed at any serious programmer or computer science student, the new second edition of Introduction to Algorithms builds on the tradition of the original with a truly magisterial guide to the world of algorithms. Clearly presented, mathematically rigorous, and yet approachable even for the maths-averse, this title sets a high standard for a textbook and reference to the best algorithms for solving a wide range of computing problems.

With sample problems and mathematical proofs demonstrating the correctness of each algorithm, this book is ideal as a textbook for classroom study, but its reach doesn't end there. The authors do a fine job at explaining each algorithm. (Reference sections on basic mathematical notation will help readers bridge the gap, but it will help to have some maths background to appreciate the full achievement of this handsome hardcover volume.) Every algorithm is presented in pseudo-code, which can be implemented in any computer language, including C/C++ and Java. This ecumenical approach is one of the book's strengths. When it comes to sorting and common data structures, from basic linked list to trees (including binary trees, red-black and B-trees), this title really shines with clear diagrams that show algorithms in operation. Even if you glance over the mathematical notation here, you can definitely benefit from this text in other ways.

The book moves forward with more advanced algorithms that implement strategies for solving more complicated problems (including dynamic programming techniques, greedy algorithms, and amortised analysis). Algorithms for graphing problems (used in such real-world business problems as optimising flight schedules or flow through pipelines) come next. In each case, the authors provide the best from current research in each topic, along with sample solutions.

This text closes with a grab bag of useful algorithms including matrix operations and linear programming, evaluating polynomials and the well-known Fast Fourier Transformation (FFT) (useful in signal processing and engineering). Final sections on "NP-complete" problems, like the well-known traveloling salesmen problem, show off that while not all problems have a demonstrably final and best answer, algorithms that generate acceptable approximate solutions can still be used to generate useful, real-world answers.

Throughout this text, the authors anchor their discussion of algorithms with current examples drawn from molecular biology (like the Human Genome project), business, and engineering. Each section ends with short discussions of related historical material often discussing original research in each area of algorithms. In all, they argue successfully that algorithms are a "technology" just like hardware and software that can be used to write better software that does more with better performance. Along with classic books on algorithms (like Donald Knuth's three-volume set, The Art of Computer Programming), this title sets a new standard for compiling the best research in algorithms. For any experienced developer, regardless of their chosen language, this text deserves a close look for extending the range and performance of real-world software. --Richard Dragan


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Customer Reviews

4.3 out of 5 stars
4.3 out of 5 stars
Most Helpful Customer Reviews
3 of 3 people found the following review helpful
3.0 out of 5 stars Good, but heqvy, textbook 11 July 2009
Format:Paperback
It's a well done book, but I have to say it's quite dry at some points, and you'll need support from others, or you can have a look on youtube for the MIT lectures that go with it.
It's a textbook clearly meant for class, which means that all answers to problems are in a separate book, which sucks for self-learners. I would be prepared to buy the answer book (or instructor book), but you have to be teacher...WTF ?
Anyway, very interesting, but also very academic.
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2 of 2 people found the following review helpful
4.0 out of 5 stars Yes, it's certainly comprehensive 2 Dec 2007
Format:Paperback
There's a limited amount you can do in a thousand pages and I reckon the authors have done what they can.

This is *not* for casual reading, it's hard work on a par with Knuth's tomes. It's not as all-inclusive as the latter, but it goes deeper into certain aspects.

The mathematical bits at the start are okay, and there is an excellent exposition on the big-oh notation (and its relatives) - such is difficult to find, for some reason. That alone makes it worth getting.

However, as a work of art it seemed somewhat amorphous to me (yes, even books on mathematics and computer science, even technical manuals, are works of art and can be judged as such), and when I got to the end, I found myself not caring too much whether the butler did it or not.

That said, if you follow through with all the exercises and problems, and manage to do them all, you look like you could have a career as a code-cutter of adequate ability.

The world needs more books like this. Bring 'em on.
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2 of 2 people found the following review helpful
5.0 out of 5 stars Sound introduction to foundational algorithms 13 May 2007
Format:Paperback
The algorithms, including the mathematical background and justification, are set out clearly. The comprehensive index makes this a useful reference. Online resources to support the book include a corrections page and an explanation of the "Professor's names" jokes scattered through the text. There is an instructor's manual but, given the widespread use of the book in formal training courses, it is not available to independent users of the book, whether students or practitioners.
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