## Introduction to AlgorithmsSome books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines 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 a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called "Divide-and-Conquer"), and an appendix on matrices. 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 for this edition. As of the third edition, this textbook is published exclusively by the MIT Press. |

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### Contents

II Sorting and Order Statistics | 146 |

III Data Structures | 228 |

IV Advanced Design and Analysis Techniques | 356 |

V Advanced Data Structures | 480 |

VI Graph Algorithms | 586 |

VII Selected Topics | 768 |

Mathematical Background | 1142 |

1231 | |

1251 | |

### Other editions - View all

Introduction to Algorithms, third edition Thomas H. Cormen,Charles E. Leiserson,Ronald L. Rivest,Clifford Stein No preview available - 2009 |

Introduction to Algorithms Thomas H. Cormen,Charles E. Leiserson,Ronald L. Rivest No preview available - 1990 |

### Common terms and phrases

algorithm amortized analysis applies array assume asymptotic attribute basic binary search tree bound Chapter child compute consider constant constraints contains corresponding cost data structure define delete denote Describe determine directed edge efficient element equal equation example execution Exercise expected factor feasible Figure flow function G D V;E Give given graph hash heap implement increase initial input insertion integer iteration least leaves Lemma length linear program loop matrix maximum method multiplication node objective operations optimal parallel perform pointer points positive probability problem procedure produce Proof prove random recursive represent requires result root running sequence shortest path Show simple solution solve sort spanning step stored subarray subproblems subtree Suppose takes Theorem tree variables vertex vertices weight