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Algorithms (4th Edition) 4th Edition

115 customer reviews
ISBN-13: 978-0321573513
ISBN-10: 032157351X
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Editorial Reviews

About the Author

Robert Sedgewick has been a Professor of Computer Science at Princeton University since 1985, where he was the founding Chairman of the Department of Computer Science. He has held visiting research positions at Xerox PARC, Institute for Defense Analyses, and INRIA, and is member of the board of directors of Adobe Systems. Professor Sedgewick’s research interests include analytic combinatorics, design and analysis of data structures and algorithms, and program visualization. His landmark book, Algorithms, now in its fourth edition, has appeared in numerous versions and languages over the past thirty years. In addition, with Kevin Wayne, he is the coauthor of the highly acclaimed textbook, Introduction to Programming in Java: An Interdisciplinary Approach (Addison-Wesley, 2008).


Kevin Wayne is the Phillip Y. Goldman Senior Lecturer in Computer Science at Princeton University, where he has been teaching since 1998. He received a Ph.D. in operations research and industrial engineering from Cornell University. His research interests include the design, analysis, and implementation of algorithms, especially for graphs and discrete optimization. With Robert Sedgewick, he is the coauthor of the highly acclaimed textbook, Introduction to Programming in Java: An Interdisciplinary Approach (Addison-Wesley, 2008).


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Product Details

  • Hardcover: 992 pages
  • Publisher: Addison-Wesley Professional; 4th edition (March 19, 2011)
  • Language: English
  • ISBN-10: 032157351X
  • ISBN-13: 978-0321573513
  • Product Dimensions: 7.6 x 1.4 x 9.2 inches
  • Shipping Weight: 3.2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (115 customer reviews)
  • Amazon Best Sellers Rank: #10,271 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

320 of 333 people found the following review helpful By Kevin P. Murphy on May 21, 2011
Format: Hardcover
"Algorithms" (4th edn) by Robert Sedgewick and Kevin Wayne (published
by Addison-Wesley in March 2011) is one of the best computer science
books I have ever read. It should be required reading for all CS
students and all programmers - it aims to cover the "50 algorithms
every programmer should know". Below I discuss some of the main
reasons why I think the book is so good.

Unlike its main rival, "An introduction to algorithms" by Cormen,
Leiserson, Rivest and Stein (CLRS), "Algorithms" contains actual
source code (written in a subset of Java). The importance of this
cannot be overstated: it means students can actually use the
algorithms to solve real problems. This enables a wealth of
interesting and motivating applications --- from web search to
genomics --- which are sprinkled throughout the book. (Source code and
data are available on the book's website.)

A natural worry with real code is that it will obscure the basic
ideas. However, by careful useful of abstract data types (classes
such as queues, bags, hash tables, trees, DAGs, etc), the authors have
done a masterful job at creating extremely concise and readable

Using real code also forces one to address important implementation
details that are easy to overlook. For example, it is well known that
mergesort requires auxiliary memory. In the CLRS pseudocode, they
allocate temporary storage space inside their merge routine. In
practice it is much more efficient to allocate temporary storage space
once, and then pass this in as a pointer to the merge function (or let
it be a private member of the mergesort class). Where else can you
learn such important tricks?
Read more ›
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75 of 81 people found the following review helpful By Let's Compare Options Preptorial TOP 500 REVIEWER on April 11, 2011
Format: Hardcover
Other reviews on this fine text are for older editions with pseudo code. Sedgewick and Wayne have completely revised this new Fourth Edition with plentiful Java scripts for a vast range of applications. A brand new website at Princeton is dedicated to this book and has visualizations, much more code, exercises, answers, bib links, full implementations of many problems, and a complete online summary and synopsis of the book.

The authors suggest this is for a second course in CS, but many serious students, whether independent or in undergrad, will find it useful for self teaching as well. In fact, the new website has self teaching resources if you are "going it alone" in your initial study of algorithms.

Algos cannot really be separated from their underlying data structures, and a serious new addition to this printing and edition is a much better backgrounder on the most up to date data structures, using hyper modern examples like Amazon and Google.

This book covers the basics, and is not an encyclopedia or reference book. It has a lot of detailed descriptions and visuals, and takes the time to be sure the student "gets" the point. In a way, it is in competition with Sedgewick's own Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching (Pts. 1-4), which is now in its third edition, and more terse, advanced and encyclopedic. If you want a thorough understanding of the whole field, you probably need both if you're just starting out in the field.

If you're a beginning programmer, and want to get into the underlying logic of sorts, searches, graphs, strings and other fundamentals that drive modeling and the web, this is the place to start.
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54 of 57 people found the following review helpful By Peter Drake on May 9, 2012
Format: Hardcover
I've recently switched to this from the Cormen et al. book for the algorithms class I teach at Lewis & Clark College (a small liberal arts college in Portland, OR). The main difference is that this book focuses on practice, where Cormen focuses more on mathematical theory. This book seems a better fit for my students and my style of teaching.

* Reasonable scope for a semester. Teaching from this book for the first time, I covered four of the six large chapters, plus part of the fifth.
* Explanations, diagrams, and examples are clear and concise.
* The authors know their stuff and don't hesitate to explain it. For example, they know why a hash table index should be computed as
(key.hashCode() & 0x7fffffff) % M
(where M is the size of the table) instead of
Math.abs(key.hashCode()) % M
* The slides provided on the book website are outstanding.
* Examples in the book and on the slides come from a wide variety of applications. They demonstrate cases where using the efficient algorithm really matters.
* One of the authors responds quickly to questions and errata. (As with any textbook, be sure to check the website and write the corrections into your copy.)

* The code does not always follow Java style conventions. For example, the authors will use non-private fields and one-letter, upper-case variable names. The many classes provided are all in the default package. It is not clear how much of this stems from deliberate decisions in the name of clarity and conciseness and how much from the authors not being "native" Java speakers.
* Some of the proofs are a bit laconic ("immediate from inspection of the code").
* The authors use an unusual ~ notation instead of the more widely-used Big-Theta/Big-O notation (although the latter is explained in passing). The ~ notation is more precise, as it does not omit the constant factor, but students may need additional practice with the standard notation.
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