Introduction to Algorithms, Second Edition Hardcover – Sep 1 2001
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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.See all Product Description
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Top Customer Reviews
- 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)
- 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.
And yes, the psuedo-code kinda [bad]. The book isn't perfect but it does what it's intended to and doesn't do what some people expect from the title. If you bought this and don't understand a word of it, keep it around and try something else first, or take classes on programming and data structures...then come back and it will make more sense.
It does not make good algorithmic use of brain-cell caloric use, sometimes.
There's a (quite) extensive list of errors on the on-line page. Please check it before going mad.
So while it seems to be a very complete book, it doesn't get the message accross with even some simple algorithms. We are all suppose to love it because it is from M.I.T., but the fact of the matter is that you'll need books more student-oriented.
Buy it for reference, anyhow. It's worth the money.
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.
Most recent customer reviews
Nice book. Reasonable price. Quite new even this is a used book.
A bit long on delivering. I like it
A decent book in regards to theory and explanations...
though, lack of solutions for certain problems which would be beneficial for learning the concepts.
a great reference book covers a wide range of algorithms in data management. the explanation is thorough and accessible, and the proofs are solid as well. Read morePublished on Aug. 20 2009 by kaiyi4
I found this book to be very good in explaining the algorithms. The language is too complicated and long-winded. Read morePublished on Sept. 16 2007 by A. Papaz
There are a number of reviewers who proclaim that the language agnostic nature of this book, in addition to it's erudite tone, more than compensate for the (artificial) learning... Read morePublished on June 21 2004 by Don Roberts
I have deep respect for math and people who can make sense out of it, but I am really slow thinker and this book simply overwelmed me. Read morePublished on June 15 2004
Giving this book a bad review because:
a) you had a bad instructor for the course
b) you find the material difficult
c) you can't understand pseudo-code
are not... Read more
It is a book that deserves more than five stars. Hard stuff, yet it is presented in a way that you get right virtually by reading. Very concise, every page very line counts.Published on Jan. 2 2004
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