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Algorithms, 4th Edition

Algorithms, 4th Edition

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Description

  • Copyright 2011
  • Dimensions: 7-3/8" x 9-1/8"
  • Pages: 992
  • Edition: 4th
  • eBook (Watermarked)
  • ISBN-10: 0-13-276258-7
  • ISBN-13: 978-0-13-276258-8

This fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms is the leading textbook on algorithms today and is widely used in colleges and universities worldwide. This book surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing--including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use.

The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts.

The companion web site, algs4.cs.princeton.edu, contains

  • An online synopsis
  • Full Java implementations
  • Test data
  • Exercises and answers
  • Dynamic visualizations
  • Lecture slides
  • Programming assignments with checklists
  • Links to related material

The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants.

Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.

Sample Content

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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