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Introduction to Algorithms

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ISBN-10: 0262032937

ISBN-13: 9780262032933

Edition: 2nd 2001

Authors: Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein

List price: $85.00
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There are books on algorithms that are rigorous but incomplete and others that cover masses of material but lack rigor. Introduction to Algorithmscombines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became the standard reference for professionals and a widely used text in universities worldwide. The second edition features new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming, as well as extensive revisions to virtually every section of the book. In a subtle but important change, loop invariants are introduced early and used throughout the text to prove algorithm correctness. Without changing the mathematical and analytic focus, the authors have moved much of the mathematical foundations material from Part I to an appendix and have included additional motivational material at the beginning.
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Book details

List price: $85.00
Edition: 2nd
Copyright year: 2001
Publisher: MIT Press
Publication date: 9/1/2001
Binding: Hardcover
Pages: 1202
Size: 8.25" wide x 9.00" long x 2.25" tall
Weight: 4.598
Language: English

Thomas H. Cormen received a Ph. D. from MIT in 1992. He is an associate professor at Dartmouth College. Cormen is one of the authors of Introduction to Algorithms.

The Role of Algorithms in Computing
Getting Started
Growth of Functions
Probabilistic Analysis and Randomized Algorithms
Sorting and Order Statistics
Sorting in Linear Time
Medians and Order Statistics
Data Structures
Elementary Data Structures
Hash Tables
Binary Search Trees
Red-Black Trees
Augmenting Data Structures
Advanced Design and Analysis Techniques
Dynamic Programming
Greedy Algorithms
Amortized Analysis
Advanced Data Structures
Binomial Heaps
Fibonacci Heaps
Data Structures for Disjoint Sets
Graph Algorithms
Elementary Graph Algorithms
Minimum Spanning Trees
Single-Source Shortest Paths
All-Pairs Shortest Paths
Maximum Flow
Selected Topics
Sorting Networks
Matrix Operations
Linear Programming
Polynomials and the FFT
Number-Theoretic Algorithms
String Matching
Computational Geometry
Approximation Algorithms
Appendix: Mathematical Background
Sets, Etc.
Counting and Probability