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  • Numerous algorithm traces throughout the book.
    • Enables students to check their understanding of the algorithm.

  • Over 1,000 end-of-section exercises—With answers to 1/3 of them in the back of the book.
    • Helps students practice solving problems.

  • More applications than other algorithms texts.
    • Provides students with applications to computer science to motivate the material.

  • Elaborate world wide web site—With up-to-date support for book. An icon occurs throughout the book to indicate more explanations and examples available on the web.
    • Provides students with expanded explanations of particular topics and additional information on algorithms.

  • Upper bounds for worst-case times proven sharp.
    • Provides students with proved sharp bounds.

  • Lower bounds integrated into sections that discuss problems—e.g. after presentation of several sorting algorithms, text discusses lower bound for comparison-based sorting.
    • Provides students with easy to follow organization.

  • Methods used to solve NP-complete problems—Including approximation, brute force, parameterized complexity, and heuristics.
    • Provides students with comprehensive chapter on topics with significant importance in algorithms.

  • Recent results—Such as Pearson's polynomial-time algorithm for the coin-changing problem and parameterized complexity.
    • Provides students with up-to-date presentation that helps motivate the material.

  • Figures and tables illustrate concepts—Figure captions provide additional explanations and insight.
    • Shows students how algorithms work to elucidate proofs.


  • Copyright 2004
  • Dimensions: 8" x 10"
  • Pages: 768
  • Edition: 1st
  • Book
  • ISBN-10: 0-02-360692-4
  • ISBN-13: 978-0-02-360692-2

Algorithms is written for an introductory upper-level undergraduate or graduate course in algorithms. With/their many years of experience in teaching algorithms courses, Richard Johnsonbaugh and Marcus Schaefer include applications of algorithms, examples, end-of-section exercises, end-of-chapter exercises, solutions to selected exercises, and notes to help the reader understand and master algorithms.

Key Features
  • Links theory to real-world applications such as data compression, region-finding in digital pictures, cellular phone networks, and the implementation of agrep.
  • Includes five chapters that emphasize design techniques: searching (including backtracking), divide and conquer, sorting, selection, the greedy method, and dynamic programming.
  • Covers distributed algorithms—a topic recommended by the ACM (2001 report) for an undergraduate curriculum.
  • Features a collection of techniques, including approximation, parameterization (a recent area of research), and use of heuristics, to deal with NP-complete problems.
  • Contains more than 1450 carefully developed and classroom-tested exercises, from routine to challenging. About one-third of the end-of-section exercises include solutions.
  • Provides a robust Companion Website that supplements the text by providing algorithm simulation software, PowerPoint® slides, late breaking news about algorithms, references about the book's topics, computer programs, and more.
  • Includes more than 300 worked examples, which provide motivation, clarify concepts, and show how to develop algorithms, demonstrate applications of the theory, and elucidate proofs.

Sample Content

Table of Contents

 1. Mathematical Prerequisites.

 2. Data Structures.

 3. Searching Techniques.

 4. Divide-and-Conquer.

 5. Sorting and Selection.

 6. Greedy Algorithms.

 7. Dynamic Programming.

 8. Text Searching.

 9. Computational Algebra.

10. P and NP.

11. Coping with NP-Completeness.

12. Parallel Algorithms.


Solutions to Selected Exercises.



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