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

Edition: 2ND 01Copyright: 2001

Publisher: MIT Press

Published: 2001

International: No

Thomas Cormen, Charles Leiserson, Ronald Rivest and Clifford Stein

Edition: 2ND 01
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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.

**Cormen, Thomas H. : Dartmouth College**

**Leiserson, Charles E. : Massachusetts Institute of Technology Rivest, Ronald L. : Massachusetts Institute of Technology Stein, Clifford : Columbia University **

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

7. Quicksort

8. Sorting in Linear Time

9. Medians and Order Statistics

11. Hash Table

12. Binary Search Trees

13. Red-Black Trees

14. Augmenting Data Structures

16. Greedy Algorithms

17. Amortized Analysis

19. Binomial Heaps

20. Fibonacci Heaps

21. Data Structures for Disjoint Sets

23. Minimum Spanning Trees

24. Single-Source Shortest Paths

25. All-Pairs Shortest Paths

26. Maximum Flow

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

B Sets, Etc.

C Counting and Probability

Bibliography

Index (created by the authors)

Summary

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.

Author Bio

**Cormen, Thomas H. : Dartmouth College**

**Leiserson, Charles E. : Massachusetts Institute of Technology Rivest, Ronald L. : Massachusetts Institute of Technology Stein, Clifford : Columbia University **

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

7. Quicksort

8. Sorting in Linear Time

9. Medians and Order Statistics

11. Hash Table

12. Binary Search Trees

13. Red-Black Trees

14. Augmenting Data Structures

16. Greedy Algorithms

17. Amortized Analysis

19. Binomial Heaps

20. Fibonacci Heaps

21. Data Structures for Disjoint Sets

23. Minimum Spanning Trees

24. Single-Source Shortest Paths

25. All-Pairs Shortest Paths

26. Maximum Flow

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

B Sets, Etc.

C Counting and Probability

Bibliography

Index (created by the authors)

Publisher Info

Publisher: MIT Press

Published: 2001

International: No

Published: 2001

International: No

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.

**Cormen, Thomas H. : Dartmouth College**

**Leiserson, Charles E. : Massachusetts Institute of Technology Rivest, Ronald L. : Massachusetts Institute of Technology Stein, Clifford : Columbia University **

**I Foundations **1. The Role of Algorithms in Computing

2. Getting Started

3. Growth of Functions

4. Recurrences

5. Probabilistic Analysis and Randomized Algorithms

7. Quicksort

8. Sorting in Linear Time

9. Medians and Order Statistics

11. Hash Table

12. Binary Search Trees

13. Red-Black Trees

14. Augmenting Data Structures

16. Greedy Algorithms

17. Amortized Analysis

19. Binomial Heaps

20. Fibonacci Heaps

21. Data Structures for Disjoint Sets

23. Minimum Spanning Trees

24. Single-Source Shortest Paths

25. All-Pairs Shortest Paths

26. Maximum Flow

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

B Sets, Etc.

C Counting and Probability

Bibliography

Index (created by the authors)