# 书籍分享–《Introduction to Algorithms Third Edition》

## 书籍简介

Introduction to Algorithms is a book by Thomas H. CormenCharles E. LeisersonRonald L. Rivest, and Clifford Stein. The book has been widely used as the textbook for algorithms courses at many universities[1] and is commonly cited as a reference for algorithms in published papers, with over 10,000 citations documented on CiteSeerX.[2] The book sold half a million copies during its first 20 years.[3] Its fame has led to the common use of the abbreviation “CLRS” (Cormen, Leiserson, Rivest, Stein), or, in the first edition, “CLR” (Cormen, Leiserson, Rivest).[4]

In the preface, the authors write about how the book was written to be comprehensive and useful in both teaching and professional environments. Each chapter focuses on an algorithm, and discusses its design techniques and areas of application. Instead of using a specific programming language, the algorithms are written in Pseudocode. The descriptions focus on the aspects of the algorithm itself, its mathematical properties, and emphasize efficiency.[5]

Introduction to Algorithms

## 书籍目录

``````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

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
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

Contents xi
VIII Appendix: Mathematical Background
Introduction
A Summations
B Sets, Etc.
C Counting and Probability
D Matrices
Bibliography
Index``````

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