Introduction To Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein

Book Summary of Introduction To Algorithms

This internationally acclaimed textbook provides a comprehensive introduction to the modern study of computer algorithms. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of read Each chapter is relatively self-contained and presents an algorithm, a design technique, an application area, or a related topic. The algorithms are described and designed in a manner 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 third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multi threaded algorithms, and substantial additions to the chapter on recurrences (now called Divide-and-Conquer ). It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many new exercises and problems have been added in this edition. The text is intended primarily for students studying algorithms or data structures. As it discusses engineering issues in algorithm design, as well as mathematical aspects, it is equally well suited for self-study by technical professionals.

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Table Of Contents
Preface
I. Foundations

• Introduction
• 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

• Introduction
• 6. Heapsort
• 7. Quicksort
• 8. Sorting in Linear Time
• 9. Medians and Order Statistics

III. Data Structures

• Introduction
• 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

• Introduction
• 15. Dynamic Programming
• 16. Greedy Algorithms
• 17. Amortized Analysis

V. Advanced Data Structures

• Introduction
• 18. B-Trees
• 19. Fibonacci Heaps
• 20. Van Emde Boas Trees
• 21. Data Structures for Disjoint Sets

VI. Graph Algorithms

• Introduction
• 22. Elementary Graph Algorithms
• 23. Minimum Spanning Trees
• 24. Single-Source Shortest Paths
• 25. All-Pairs Shortest Paths
• 26. Maximum Flow

VII. Selected Topics

• Introduction
• 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

• Introduction
• A. Summations
• B. Sets etc.
• C. Counting and Probability
• D. Matrices

Bibliography
Index

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Categories: Computer and Internet