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Introduction to Algorithms, Second Edition Hardcover – Sep 1 2001


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Introduction to Algorithms
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Product Details

  • Hardcover: 1202 pages
  • Publisher: The MIT Press; 2 edition (Sept. 1 2001)
  • Language: English
  • ISBN-10: 0262032937
  • ISBN-13: 978-0262032933
  • Product Dimensions: 20.3 x 5.7 x 22.9 cm
  • Shipping Weight: 2.1 Kg
  • Average Customer Review: 3.9 out of 5 stars  See all reviews (46 customer reviews)
  • Amazon Bestsellers Rank: #197,218 in Books (See Top 100 in Books)
  • See Complete Table of Contents

Product Description

From Amazon

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

From the Publisher

There are books on algorithms that are rigorous but incomplete and others that cover masses of material but lack rigor. Introduction to Algorithms 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 the standard reference for professionals and a widely used text in universities worldwide. The 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.


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Customer Reviews

3.9 out of 5 stars

Most helpful customer reviews

5 of 5 people found the following review helpful By S. Saha on Feb. 23 2004
Format: Hardcover
You shouldn't have to read this review... this book is unmatched in it's field - it's a great book for someone with no background in algorithms to start learning. The exercises are very interesting with some being more mathematical while others are thought provoking extensions to material covered in the book. It's easily the bible in this field. After this one can go on to more advanced specialized material like Papadimitriou, Motwani and Raghavan etc. If you don't have this book and you work with ANY kind of algorithms or do any kind of programming, you owe it to yourself to get it.
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4 of 4 people found the following review helpful By A Customer on July 30 2003
Format: Hardcover
Pros:
- Good general book for basic algorithm stuff.
- Tons of basic algorithms.
- Thorough in proofs.
- Very easy to follow once in case you have enough Math background (by either being a grad student or else if undergrad, read the first few chapters as well as Appendices well in advance to the course (Spend time solving the exercises and get familiar with the notation etc. before taking the course)
Cons:-
- I don't consider it a good idea to write algorithms with index starting from 1 instead of 0? Most popular languages used in the industry, have arrays starting from zero.
- Most professors that I have discussed it with agree that this is not the best book for the subject but probably the only one with this much material in it.
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Format: Hardcover
While many have noted how Thomas Corwen and his co-authors have added a scholarly touch to this subject with plenty of proofs it does not make for a good text. One can argue that this book should supplement the instructor's teachings. That would be fine except for the fact that there are no answers to the problems. Therefore, a student has no idea if he or she is on the right track.
To this end Corwen snidely replies on his website that any student asking for the answer will have his or her name posted as a potential cheater since Corwen believes that instructors should be able to use his problems as homework. Here's an idea, how about instructors developing their own problems!
Corwen also does not relate the material in plain English as someone like Frank Carrano does. There are other sources of many of the concepts like binary search trees, sorting algorithms, O-notation. The only thing Corwen is adding is lots of proof and mathematical shorthand.
If you are interested in the mathematical concepts behind the algorithms this is a fine introduction. If you are interested in the algorithmic concepts, this is not for you. Ultimately if you are a student whose instructor will be using this book, you have no choice about buying it. If you are an instructor, however, look at another book to supplement your teachings.
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Format: Hardcover
I purchased the book because it was required for my undergraduate algorithm analysis class. My experience so far has been terrible. My instructor was incapable of getting across even the basic concepts and he was constantly making mistakes and backpedaling. It didn't help either that he didn't make the slides used in the class and only saw them for the first time when he walked into the class. All of this and a weak background preparatory at the beginning of the class made the book a rather excruciating book to learn from. It is indeed a book of depth and knowledge, but it can be used against you as easily as it can be used for your advancement. Due to my bad experience, I'm inclined to look at CLR rather negatively. I would dearly love to take another algorithm class with a truely competent instructor but since there isn't one in my immediate future, it'll be a while before I'm given a chance to revise my opinion of the book.
The book can be an excellent source of algorithmatic knowledge but it's hardly an "introduction" for the beginners and used wrong will very easily dampen any futher computer science ambitions.
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Format: Hardcover
this is possibly the best book for the course 'Data structures and analysis of algorithms'.Knuth is far too advanced and many others are not even worth mentioning.
The best part is that it is very perspicuous but does not compromise on mathematical rigour.The proofs of correctness are very elegant as are the detalied analyses of all the algorithms.Actually,the mathematical approach that the authors employ is very enjoyable.A full section devoted to the mathematical tools is a very good idea.
All the topics viz. data structures, sorting techniques,graphs,design techniques like dynamic programming,greedy algorithms,Divide-n-conquer r given in extensive detail.(since i m only a second yr under grad student,i havent read the more advanced topics like FFT,computational geometry,NP-completeness.)
The exercises make you think and test both mathematical acumen and programming dexterity.many of them require a fair bit of creativity.
As another reviewer pointed out, this book is the one for budding computer scientists and software engineers,not for the 'learn XYZ in 21 hours' fans.
a bit of background in a structured programming language(Pascal ,C etc.) and more importantly,knowledge of the fundamentals of discrete mathematics is required.
A must buy for all CS students.
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Format: Hardcover
I had heard much about this book before I purchased it but since it was never required I had never actually looked at it until recently.
Well its reputation is well deserved. This book is certainly COMPREHENSIVE if nothing else. I cannot imagine a common algorithm that is not explained and analyzed in this book, from Discrete Fourier Transform to Computational Geometry it is all here.
Also I like the fact that the material is presented in such a way that it is easy to study by yourself. The style is informal, and although rigorous proofs are also provided the emphasis is on the intuition behind the algorithm.
There are substantial appendices and an easy introduction section, such that you need very little mathematical background at all to be able to benefit from this text.
Overall, I cannot imagine that there is another algorithms textbook that is as comprehensive and rigorous as this one.
The only downside is that it is very hefty and correspondingly expensive. But if you are a novice in algorithms and want an easy to follow text I can highly recommend it.
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