Introduction to Algorithms / Edition 2

by Thomas Cormen, Clifford Stein, Ronald Rivest, Charles Leiserson

Overview

The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures. Like the first edition, this text can also be used for self-study by technical professionals since it discusses engineering issues in algorithm design as well as the mathematical aspects.

In its new edition, Introduction to Algorithms continues to provide a comprehensive introduction to the modern study of algorithms. The revision has been updated to reflect changes in the years since the book's original publication. New chapters on the role of algorithms in computing and on probabilistic analysis and randomized algorithms have been included. Sections throughout the book have been rewritten for increased clarity, and material has been added wherever a fuller explanation has seemed useful or new information warrants expanded coverage.

As in the classic first edition, this new edition of Introduction to Algorithms presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers. Further, the algorithms are presented in pseudocode to make the book easily accessible to students from all programming language backgrounds.

Each chapter presents an algorithm, a design technique, an application area, or a related topic. The chapters are not dependent on one another, so the instructor can organize his or her use of the book in the way that best suits the course's needs. Additionally, the new edition offers a 25% increase over the first edition in the number of problems, giving the book 155 problems and over 900 exercises that reinforce the concepts the students are learning.

Product Details

ISBN-13:	9780070131514
Publisher:	McGraw-Hill Companies, The
Publication date:	07/16/2001
Edition description:	New Edition
Pages:	1180
Product dimensions:	8.20(w) x 9.30(h) x 2.30(d)

About the Author

Thomas H. Cormen is Assistant Professor in the Department of Computer Science at Dartmouth College.

Charles E. Leiserson is Professor and head of the Supercomputing Technologies Group at the Laboratory for Computer Science at MIT.

Ronald L. Rivest is the Webster Professor of Electrical Engineering and Computer Science in the Department of Electrical Engineering and Computer Science and Associate Director of the Laboratory for Computer Science at MIT.

Table of Contents

Preface
I Foundations
1 The Role of Algorithms in Computing
2 Getting Started
3 Growth of Functions
4 Recurrences
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 Table
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 Binomial Heaps
20 Fibonacci Heaps
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 Sorting Networks
28 Matrix Operations
29 Linear Programming
30 Polynomials and the FFT
31 Number-Theoretic Algorithms
32 String Matching
33 Computational Geometry
(and more...)

Editorial Reviews

Both rigorous and complete, this introduction covers traditional material and modern developments: elementary data structures, sorting graph algorithms and NP-completeness are included along with material on Fibonacci heaps, parallel algorithms, network flow algorithms, computational geometry, and number-theoretic algorithms. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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