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数据结构与算法分析(C++版) 第三版 英文版

数据结构与算法分析(C++版) 第三版 英文版

作者:Clifford
出版社:电子工业出版社出版时间:2019-08-01
开本: 大16开 页数: 594
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数据结构与算法分析(C++版) 第三版 英文版 版权信息

数据结构与算法分析(C++版) 第三版 英文版 内容简介

  《数据结构与算法分析(C++版 第3版 英文版)/国外计算机科学教材系列》采用程序员爱用的面向对象C++语言来描述数据结构和算法,并把数据结构原理和算法分析技术有机地结合在一起,系统介绍了各种类型的数据结构和排序、检索的各种方法。作者非常注意对每一种数据结构的不同存储方法及有关算法进行分析比较。书中还引人了一些比较高级的数据结构与先进的算法分析技术,并介绍了可计算性理论的一般知识。书中分别给出了C++实现方法和伪码实现方法,便于读者根据情况选择。《数据结构与算法分析(C++版 第3版 英文版)/国外计算机科学教材系列》作者维护的网站上可下载相关代码、编程项目和辅助练习资料。  《数据结构与算法分析(C++版 第3版 英文版)/国外计算机科学教材系列》适合作为大专院校计算机软件专业与计算机应用专业学生的教材和参考书,也适合计算机工程技术人员参考。

数据结构与算法分析(C++版) 第三版 英文版 目录

Ⅰ Preliminaries
1 Data Structures and Algorithms
1.1 A Philosophy of Data Structures
1.1.1 The Need for Data Structures
1.1.2 Costs and Benefits
1.2 Abstract Data Types and Data Structures
1.3 Design Patterns
1.3.1 Flyweight
1.3.2 Visitor
1.3.3 Composite
1.3.4 Strategy
1.4 Problems, Algorithms, and Programs
1.5 Further Reading
1.6 Exercises
2 Mathematical Preliminaries
2.1 Sets and Relations
2.2 Miscellaneous Notation
2.3 Logarithms
2.4 Summations and Recurrences
2.5 Recursion
2.6 Mathematical Proof Techniques
2.6.1 Direct Proof
2.6.2 Proof by Contradiction
2.6.3 Proof by Mathematical Induction
2.7 Estimation
2.8 Further Reading
2.9 Exercises
3 Algorithm Analysis
3.1 Introduction
3.2 Best, Worst, and Average Cases
3.3 A Faster Computer, or a Faster Algorithm?
3.4 Asymptotic Analysis
3.4.1 Upper Bounds
3.4.2 Lower Bounds
3.4.3 Notation
3.4.4 Simplifying Rules
3.4.5 Classifying Functions
3.5 Calculating the Running Time for a Program
3.6 Analyzing Problems
3.7 Common Misunderstandings
3.8 Multiple Parameters
3.9 Space Bounds
3.10 Speeding Up Your Programs
3.11 Empirical Analysis
3.12 Further Reading
3.13 Exercises
3.14 Projects

Ⅱ Fundamental Data Structures
4 Lists, Stacks, and Queues
4.1 Lists
4.1.1 Array-Based List Implementation
4.1.2 Linked Lists
4.1.3 Comparison of List Implementations
4.1.4 Element Implementations
4.1.5 Doubly Linked Lists
4.2 Stacks
4.2.1 Array-Based Stacks
4.2.2 Linked Stacks
4.2.3 Comparison of Array-Based and Linked Stacks
4.2.4 Implementing Recursion
4.3 Queues
4.3.1 Array-Based Queues
4.3.2 Linked Queues
4.3.3 Comparison of Array-Based and Linked Queues
4.4 Dictionaries
4.5 Further Reading
4.6 Exercises
4.7 Projects
5 Binary Trees
5.1 Definitions and Properties
5.1.1 The Full Binary Tree Theorem
5.1.2 A Binary Tree Node ADT
5.2 Binary Tree Traversals
5.3 Binary Tree Node Implementations
5.3.1 Pointer-Based Node Implementations
5.3.2 Space Requirements
5.3.3 Array Implementation for Complete Binary Trees
5.4 Binary Search Trees
5.5 Heaps and Priority Queues
5.6 Huffman Coding Trees
5.6.1 Building Huffman Coding Trees
5.6.2 Assigning and Using Huffman Codes
5.6.3 Search in Huffman Trees
5.7 Further Reading
5.8 Exercises
5.9 Projects
6 Non-Binary Trees
6.1 General Tree Definitions and Terminology
6.1.1 An ADT for General Tree Nodes
6.1.2 General Tree Traversals
6.2 The Parent Pointer Implementation
6.3 General Tree Implementations
6.3.1 List of Children
6.3.2 The Left-Child/Right-Sibling Implementation
6.3.3 Dynamic Node Implementations
6.3.4 Dynamic “Left-Child/Right-Sibling” Implementation
6.4 K-ary Trees
6.5 Sequential Tree Implementations
6.6 Further Reading
6.7 Exercises
6.8 Projects

Ⅲ Sorting and Searching
7 Internal Sorting
7.1 Sorting Terminology and Notation
7.2 Three□(n2) Sorting Algorithms
7.2.1 Insertion Sort
7.2.2 Bubble Sort
7.2.3 Selection Sort
7.2.4 The Cost of Exchange Sorting
7.3 Shellsort
7.4 Mergesort
7.5 Quicksort
7.6 Heapsort
7.7 Binsort and Radix Sort
7.8 An Empirical Comparison of Sorting Algorithms
7.9 Lower Bounds for Sorting
7.10 Further Reading
7.11 Exercises
7.12 Projects
8 File Processing and External Sorting
8.1 Primary versus Secondary Storage
8.2 Disk Drives
8.2.1 Disk Drive Architecture
8.2.2 Disk Access Costs
8.3 Buffers and Buffer Pools
8.4 The Programmer’s View of Files
8.5 External Sorting
8.5.1 Simple Approaches to External Sorting
8.5.2 Replacement Selection
8.5.3 Multiway Merging
8.6 Further Reading
8.7 Exercises
8.8 Projects
9 Searching
9.1 Searching Unsorted and Sorted Arrays
9.2 Self-Organizing Lists
9.3 Bit Vectors for Representing Sets
9.4 Hashing
9.4.1 Hash Functions
9.4.2 Open Hashing
9.4.3 Closed Hashing
9.4.4 Analysis of Closed Hashing
9.4.5 Deletion
9.5 Further Reading
9.6 Exercises
9.7 Projects
10 Indexing
10.1 Linear Indexing
10.2 ISAM
10.3 Tree-based Indexing
10.4 2-3 Trees
10.5 B-Trees
10.5.1 B+-Trees
10.5.2 B-Tree Analysis
10.6 Further Reading
10.7 Exercises
10.8 Projects

Ⅳ Advanced Data Structures
11 Graphs
11.1 Terminology and Representations
11.2 Graph Implementations
11.3 Graph Traversals
11.3.1 Depth-First Search
11.3.2 Breadth-First Search
11.3.3 Topological Sort
11.4 Shortest-Paths Problems
11.4.1 Single-Source Shortest Paths
11.5 Minimum-Cost Spanning Trees
11.5.1 Prim’s Algorithm
11.5.2 Kruskal’s Algorithm
11.6 Further Reading
11.7 Exercises
11.8 Projects
12 Lists and Arrays Revisited
12.1 Multilists
12.2 Matrix Representations
12.3 Memory Management
12.3.1 Dynamic Storage Allocation
12.3.2 Failure Policies and Garbage Collection
12.4 Further Reading
12.5 Exercises
12.6 Projects
13 Advanced Tree Structures
13.1 Tries
13.2 Balanced Trees
13.2.1 The AVL Tree
13.2.2 The Splay Tree
13.3 Spatial Data Structures
13.3.1 The K-D Tree
13.3.2 The PR quadtree
13.3.3 Other Point Data Structures
13.3.4 Other Spatial Data Structures
13.4 Further Reading
13.5 Exercises
13.6 Projects

Ⅴ Theory of Algorithms
14 Analysis Techniques
14.1 Summation Techniques
14.2 Recurrence Relations
14.2.1 Estimating Upper and Lower Bounds
14.2.2 Expanding Recurrences
14.2.3 Divide and Conquer Recurrences
14.2.4 Average-Case Analysis of Quicksort
14.3 Amortized Analysis
14.4 Further Reading
14.5 Exercises
14.6 Projects
15 Lower Bounds
15.1 Introduction to Lower Bounds Proofs
15.2 Lower Bounds on Searching Lists
15.2.1 Searching in Unsorted Lists
15.2.2 Searching in Sorted Lists
15.3 Finding the Maximum Value
15.4 Adversarial Lower Bounds Proofs
15.5 State Space Lower Bounds Proofs
15.6 Finding the ith Best Element
15.7 Optimal Sorting
15.8 Further Reading
15.9 Exercises
15.10 Projects
16 Patterns of Algorithms
16.1 Dynamic Programming
16.1.1 The Knapsack Problem
16.1.2 All-Pairs Shortest Paths
16.2 Randomized Algorithms
16.2.1 Randomized algorithms for finding large values
16.2.2 Skip Lists
16.3 Numerical Algorithms
16.3.1 Exponentiation
16.3.2 Largest Common Factor
16.3.3 Matrix Multiplication
16.3.4 Random Numbers
16.3.5 The Fast Fourier Transform
16.4 Further Reading
16.5 Exercises
16.6 Projects
17 Limits to Computation
17.1 Reductions
17.2 Hard Problems
17.2.1 The Theory of NP-Completeness
17.2.2 NP-Completeness Proofs
17.2.3 Coping with NP-Complete Problems
17.3 Impossible Problems
17.3.1 Uncountability
17.3.2 The Halting Problem Is Unsolvable
17.4 Further Reading
17.5 Exercises
17.6 Projects

Ⅵ APPENDIX
A Utility Functions
Bibliography
Index
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