算法技术手册 影印版第二版 乔治·T·海涅曼 程序软件技术 东南大学出版社 新华书店正版图书籍 大中专教材

Preface to the Second Edition

1. Thinking in Algorithms

Understand the Problem

Naive Solution

Intelligent Approaches

Summary

References

2. The Mathematics of Algorithms

Size of a Problem Instance

Rate of Growth of Functions

Analysis in the Best， Average， and Worst Cases

Performance Families

Benchmark Operations

References

3. Algorithm Building Blocks

Algorithm Template Format

Pseudocode Template Format

Empirical Evaluation Format

Floating-Point Computation

Example Algorithm

Common Approaches

References

4. Sorting Algorithms

Transposition Sorting

Selection Sort

Heap Sort

Partition-Based Sorting

Sorting without Comparisons

Bucket Sort

Sorting with Extra Storage

String Benchmark Results

Analysis Techniques

References

5. Searching

Sequential Search

Binary Search

Hash-Based Search

Bloom Filter

Binary Search Tree

References

6. Graph Algorithms

Graphs

Depth-First Search

Breadth-First Search

Single-Source Shortest Path

Dijkstra's Algorithm for Dense Graphs

Comparing Single-Source Shortest-Path Options

All-Pairs Shortest Path

Minimum Spanning Tree Algorithms

Final Thoughts on Graphs

References

7. Path Finding in AI

Game Trees

Path-Finding Concepts

Minimax

NegMax

AlphaBeta

Search Trees

Depth-First Search

Breadth-First Search

A'Search

Comparing Search-Tree Algorithms

References

8. Network Flow Algorithms

Network Flow

Maximum Flow

Bipartite Matching

Reflections on Augmenting Paths

Minimum Cost Flow

Transshipment

Transportation

Assignment

Linear Programming

References

9. Computational Ge0metry

Classifying Problems

Convex Hull

Convex Hull Scan

Computing Line-Segment Intersections

LineSweep

Voronoi Diagram

References

10. Spatial Tree Structures

Nearest Neighbor Queries

Range Queries

Intersection Queries

Spatial Tree Structures

Nearest Neighbor Queries

Range Query

Quadtrees

R-Trees

References

11. Emerging Algorithm Categories

Variations on a Theme

Approximation Algorithms

Parallel Algorithms

Probabilistic Algorithms

References

12. Epilogue： Principles of Algorithms

Know Your Data

Decompose a Problem into Smaller Problems

Choose the Right Data Structure

Make the Space versus Time Trade-Off

Construct a Search

Reduce Your Problem to Another Problem

Writing Algorithms Is Hard-Testing Algorithms Is Harder

Accept Approximate Solutions When Possible

Add Parallelism to Increase Performance

A. Benchmarking

Index

开发健壮的软件需要高效的算法，但是程序员们很少能够理解可用方案的适用范围。
《算法技术手册（影印版 第2版 英文版）》讲解了各种可用于解决各种编码问题的现有算法，可以帮助你作出正确的选择和实现——只需要一般程度的数学知识就足以使你理解并分析算法的性能。
较之理论而言，《算法技术手册（影印版 第2版 英文版）》专注于应用。书中本着严谨细致的原则，提供了用法说明以及由多种语言实现的真实代码。这一版的更新内容包括一些新算法的Python实现、维诺图的实现以及有关空间树结构的全新章节，比如R树和四叉树。

 作者简介

作者:(美)乔治·T·海涅曼 作者:加里·波利斯 作者:斯坦利·塞克欧
乔治·T·海涅曼，伍斯特理工学院计算机科学系副教授，他还担任了2005年基于组件的软件工程国际研讨会的议程主席。加里·波利斯，伍斯特理工学院实践教授，他还是《Head First Object-0rlented Analysis and Desigrl》一书的合著者。斯坦利·塞克欧，在将近四十年的时间里，先后在Knoxville伍斯特、蒙特利尔、重庆、洛桑以及巴黎的数所大学中任教。