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Algorithms, 4th Edition

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Product Author Bios

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).

Essential Information about Algorithms and Data Structures

 

A Classic Reference

The latest version of Sedgewick’s best-selling series, reflecting an indispensable body of knowledge developed over the past several decades.

 

Broad Coverage

Full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing, including fifty algorithms every programmer should know. See algs4.cs.princeton.edu/code.

 

Completely Revised Code

New Java implementations written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use.

 

Engages with Applications

Algorithms are studied in the context of important scientific, engineering, and commercial applications. Clients and algorithms are expressed in real code, not the pseudo-code found in many other books.

 

Intellectually Stimulating

Engages reader interest with clear, concise text, detailed examples with visuals, carefully crafted code, historical and scientific context, and exercises at all levels.

 

A Scientific Approach

Develops precise statements about performance, supported by appropriate mathematical models and empirical studies validating those models.

 

Integrated with the Web

Visit algs4.cs.princeton.edu for a freely accessible, comprehensive Web site, including text digests, program code, test data, programming projects, exercises, lecture slides, and other resources.

 

Contents

Chapter 1: Fundamentals

Programming Model

Data Abstraction

Bags, Stacks, and Queues

Analysis of Algorithms

Case Study: Union-Find

 

Chapter 2: Sorting

Elementary Sorts

Mergesort

Quicksort

Priority Queues

Applications

 

Chapter 3: Searching

Symbol Tables

Binary Search Trees

Balanced Search Trees

Hash Tables

Applications

 

Chapter 4: Graphs

Undirected Graphs

Directed Graphs

Minimum Spanning Trees

Shortest Paths

 

Chapter 5: Strings

String Sorts

Tries

Substring Search

Regular Expressions

Data Compression

 

Chapter 6: Context

Author's Site

Please visit the author's website.

Customer Reviews

186 of 195 people found the following review helpful
5.0 out of 5 stars Best algorithms textbook by far, May 21, 2011
By 
Kevin P. Murphy (Vancouver, BC) - See all my reviews
(REAL NAME)   
This review is from: Algorithms (4th Edition) (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... Read more
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41 of 45 people found the following review helpful
5.0 out of 5 stars Updated Review For Fourth Edition, April 11, 2011
This review is from: Algorithms (4th Edition) (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... Read more
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25 of 28 people found the following review helpful
5.0 out of 5 stars Good introductory text, October 14, 2004
By 
Bjørn Borud (Trondheim, Norway) - See all my reviews
(REAL NAME)   
This review is from: Algorithms (Hardcover)
I found this book at a university book shop back when I was 14 years old and bought it to learn more about certain algorithms. The reason I bought it was because it looked like it would provide very concrete advice on how to achieve an implementation while not requiring more advanced mathematics than I knew at the time.

Now, many years later I have to say that I can't think of any algorithm book I've come across that manages to balance theory and concrete solutions so well; and I own quite a few books on algorithms. (Some might object to the fact that the book uses Pascal as the implementation language, but I think I've seen this book tailored for other languages too).

Also, for a general book on algorithms, Sedgewick managed to pick a very good mix of topics to cover. According to a friend of mine (whom happens to know Sedgewick personally), the book just represents a cross-section of what Sedgewick himself was interested in.

This book was very... Read more
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Table of Contents

Preface viii

 

Chapter 1: Fundamentals 3

1.1 Basic Programming Model 8

1.2 Data Abstraction 64

1.3 Bags, Queues, and Stacks 120

1.4 Analysis of Algorithms 172

1.5 Case Study: Union-Find 216

 

Chapter 2: Sorting 243

2.1 Elementary Sorts 244

2.2 Mergesort 270

2.3 Quicksort 288

2.4 Priority Queues 308

2.5 Applications 336

 

Chapter 3: Searching 361

3.1 Symbol Tables 362

3.2 Binary Search Trees 396

3.3 Balanced Search Trees 424

3.4 Hash Tables 458

3.5 Applications 486

 

Chapter 4: Graphs 515

4.1 Undirected Graphs 518

4.2 Directed Graphs 566

4.3 Minimum Spanning Trees 604

4.4 Shortest Paths 638

 

Chapter 5: Strings 695

5.1 String Sorts 702

5.2 Tries 730

5.3 Substring Search 758

5.4 Regular Expressions 788

5.5 Data Compression 810

 

Chapter 6: Context 853

 

Index 933

List of Algorithms 954

List of Clients 955

 
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