Introduction to Algorithms

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Introduction to Algorithms
Clrs3.jpeg
Cover of the third edition
Author Thomas H. Cormen
Charles E. Leiserson
Ronald L. Rivest
Clifford Stein
Country  United States
Language English
Subject Computer algorithms
Publisher MIT Press
Publication date
1990 (first edition)
Pages 1292
ISBN 978-0-262-03384-8

Introduction to Algorithms is a book by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. It is used as the textbook for algorithms courses at many universities and is commonly cited as a reference for algorithms in published papers, with over 8900 citations documented on CiteSeerX.[1] The book sold half a million copies during its first 20 years.[2] Its fame has led to the common use of the abbreviation "CLRS" (Cormen, Leiserson, Rivest, Stein), or, in the first edition, "CLR" (Cormen, Leiserson, Rivest).[3]

Editions

The first edition of the textbook did not include Stein as an author, and thus the book became known by the initialism CLR. After the addition of the fourth author in the second edition, many began to refer to the book as "CLRS". This first edition of the book was also known as "The Big White Book (of Algorithms)." With the second edition, the predominant color of the cover changed to green, causing the nickname to be shortened to just "The Big Book (of Algorithms)."[4] A third edition was published in August 2009.

CD-ROM

The second edition of the book published by McGraw-Hill is available with a companion CD-ROM including examples in Java.

Cover design

The mobile depicted on the cover, Big Red (1959) by Alexander Calder, can be found at the Whitney Museum of American Art in New York City.[5]

Table of Contents

  • I Foundations
    • 1 The Role of Algorithms in Computing
    • 2 Getting Started
    • 3 Growth of Functions
    • 4 Divide-and-Conquer
    • 5 Probabilistic Analysis and Randomized Algorithms
  • II Sorting and Order Statistics
    • 6 Heapsort
    • 7 Quicksort
    • 8 Sorting in Linear Time
    • 9 Medians and Order Statistics
  • III Data Structures
    • 10 Elementary Data Structures
    • 11 Hash Tables
    • 12 Binary Search Trees
    • 13 Red-Black Trees
    • 14 Augmenting Data Structures
  • IV Advanced Design and Analysis Techniques
    • 15 Dynamic Programming
    • 16 Greedy Algorithms
    • 17 Amortized Analysis
  • V Advanced Data Structures
    • 18 B-Trees
    • 19 Fibonacci Heaps
    • 20 van Emde Boas Trees
    • 21 Data Structures for Disjoint Sets
  • VI Graph Algorithms
    • 22 Elementary Graph Algorithms
    • 23 Minimum Spanning Trees
    • 24 Single-Source Shortest Paths
    • 25 All-Pairs Shortest Paths
    • 26 Maximum Flow
  • VII Selected Topics
    • 27 Multithreaded Algorithms
    • 28 Matrix Operations
    • 29 Linear Programming
    • 30 Polynomials and the FFT
    • 31 Number-Theoretic Algorithms
    • 32 String Matching
    • 33 Computational Geometry
    • 34 NP-Completeness
    • 35 Approximation Algorithms
  • VIII Appendix: Mathematical Background
    • A Summations
    • B Sets, Etc.
    • C Counting and Probability
    • D Matrices

Publication history

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References

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  4. Neato Tech Books (J. Blustein)
  5. Cormen et al, back cover. See, also, Big Red at the Whitney Museum of American Art web site.

External links

  • MIT lecture "MIT 6.046J / 18.410J Introduction to Algorithms - Fall 2005". Held in part by coauthor Charles Leiserson. Released as part of MIT OpenCourseWare.
    • At OCW.MIT.Edu. Video recordings and transcripts of the lectures.
    • At VideoLectures.Net. Video recordings of the lectures. Includes slides automatically synchronized to video content.

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