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数据结构与算法分析（Java版 英文原版）
作者：（美）Clifford A.Shaffer著
出版社：电子工业出版社
出版时间：2002-05-01
ISBN：9787505375819
定价：¥39.00
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内容简介
本书采用了当前十分流行且适合于Internet环境的面向对象程序设计语言Java作为算法描述语言。本书利用Java的接口来定义抽象数据类型，这比使用C++的类更自然。本书把数据结构原理和算法分析技术有机地结合在一起，系统地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。本书还引入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。本书概念清楚，逻辑性强，内容新颖，可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，也可供计算机工程技术人员参考。
作者简介
暂缺《数据结构与算法分析（Java版 英文原版）》作者简介
目录
Preface
Part I Preliminaries
Chapter 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
1.1.3 Goals of This Book
1.2 Abstract Data Types and Data Structures
1.3 Problems,Algorithms,and Programs
1.4 Algorithm Efficiency
1.5 Further Reading
1.6 Exercises
Chapter 2 Mathematical Preliminaries
2.1 Sets
2.2 Miscellaneous Notation
2.3 Logarithms
2.4 Recursion
2.5 Summations and Recurrences
2.6 Mathematical Proof Techniques
2.6.1 Proof by Contradiction
2.6.2 Proof by Mathematical Induction
2.7 Estimating
2.8 Further Reading
2.9 Exercises
Chapter 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 Q Notation
3.4.4 Simplifying Rules
3.5 calculating the Running Time of a Program
3.6 Analyzing Problems
3.7 Multiple Parameters
3.8 Space Bounds
3.9 Some Practical Considerations
3.10 Further Reading
3.11 Exercises
3.12 Projects
Part II fundamental Data Structures
Chapter 4 Lists,Stacks,and Queues
4.1 Lists
4.1.1 Array-Based List Implementation
4.1.2 Linked List
4.1.3 Comparison of List Implementations
4.1.4 Element Implementations
4.1.5 Doubly Linked List
4.1.6 Circular 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 Exercises
4.5 Projects
Chapter 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 Implementations
5.3.1 Pointer-Based Node Implementations
5.3.2 Space Requirements
5.3.3 Array Implementation for Complete Binary Trees
5.4 Huffman Coding Trees
5.4.1 Building Huffman Coding Trees
5.4.2 Assigning and Using Huffman Codes
5.5 Binary Search Trees
5.6 Heaps and Priority Queues
5.7 Further Reading
5.8 Exercises
5.9 Projects
Chapter 6 General 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
Chapter 7 Graphs
7.1 Terminology and Representations
7.2 Graph Implementations
7.3 Graph Traversals
7.3.1 Depth-First Search
7.3.2 Breadth-First Search
7.3.3 Topological Sort
7.4 Shortest-Paths Problems
7.4.1 Single-Source Shortest Paths
7.4.2 All-Pairs Shortes Paths
7.5 Minimum-Cost Spanning Trees
7.5.1 Prim's Algorithm
7.5.2 Kruskal;s Algorithm
7.6 Further Reading
7.7 Exercises
7.8 Projects
Part III Sorting and Searching
Chapter 8 Internal Sorting
8.1 sorting Terminology and Notation
8.2 Three Sorting Algorithms
8.2.1 Insertion Sort
8.2.2 Bubble Sort
8.2.3 Selection Sort
8.2.4 The Cost of Exchange Sorting
8.3 Shellsort
8.4 Quicksort
8.5 Mergesort
8.6 Heapsort
8.7 Binsort and Radix Sort
8.8 An Empirical Comparison of Sorting Algorithms
8.9 Lower Bounds for Sorting
8.10 Further Reading
8.11 Exercises
8.12 Projects
Chapter 9 File Processing and External Sorting
9.1 Primary Versus Secondary Storage
9.2 Disk and Tape Drives
9.2.1 Disk Access Costs
9.2.2 Magnetic Tape
9.3 Buffers and Buffer Pools
9.4 The Programmer's View of Files
9.5 External Sorting
9.6 Simple Approaches to External Sorting
9.7 Replacement Selection
9.8 Multiway Merging
9.9 Further Reading
9.10 Exercises
9.11 Projects
Chapter 10 Searching
10.1 Searching Sorted Arrays
10.2 Self-Organizing Lists
10.3 Searching in Sets
10.4 Hashing
10.4.1 Hash Functions
10.4.2 Open Hashing
10.4.3 Closed Hashing
10.5 Further Reading
10.6 Exercises
10.7 Projects
Chapter 11 Indexing
11.1 Linear Indexing
11.2 ISAM
11.3 Tree Indexing
11.4 2-3 Trees
11.5 B-Trees
11.5.1 B+-Trees
11.5.2 B-Tree Analysis
11.6 Further Reading
11.7 Exercises
11.8 Projects
Part IV Applications and Advanced Topics
Chapter 12 Lists and Arrays Revisited
12.1 Skip Lists
12.2 Multilists
12.3 Matrix Representations
12.4 Memory Management
12.4.1 Dynamic Storage Allocation
12.4.2 Failure Policies and Garbage Collection
12.5 Further Reading
12.6 Exercises
12.7 Projects
Chapter 13 Advanced Tree Structures
13.1 Tries
13.2 Splay Trees
13.3 Spatial Data Structures
13.3.1 The K-D Tree
13.3.2 The PR quadtree
13.3.3 Other Spatial Data Structures
13.4 Further Reading
13.5 Exercises
13.6 Projects
Chapter 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
Chapter 15 Limits to Computation
15.1 Introduction
15.2 Reductions
15.3 Hard Problems
15.3.1 NP-Completeness
15.3.2 Getting Around NP-Complete Problems
15.4 Impossible Problems
15.4.1 Uncountability
15.4.2 The Halting Problem is Unsolvable
15.4.3 Determining Program Behavior is Unsolvable
15.5 Further Reading
15.6 Exercises
15.7 Projects
Part V Appendix
Appendix A Java Tutorial for C and Pascal Programmers
A.1 Example 1：Interface for Lists
A.2 Example 2：Array-Based List Implementation
A.3 Example 3：Linked List Implementation
Bibliography
Part I Preliminaries
Chapter 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
1.1.3 Goals of This Book
1.2 Abstract Data Types and Data Structures
1.3 Problems,Algorithms,and Programs
1.4 Algorithm Efficiency
1.5 Further Reading
1.6 Exercises
Chapter 2 Mathematical Preliminaries
2.1 Sets
2.2 Miscellaneous Notation
2.3 Logarithms
2.4 Recursion
2.5 Summations and Recurrences
2.6 Mathematical Proof Techniques
2.6.1 Proof by Contradiction
2.6.2 Proof by Mathematical Induction
2.7 Estimating
2.8 Further Reading
2.9 Exercises
Chapter 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 Q Notation
3.4.4 Simplifying Rules
3.5 calculating the Running Time of a Program
3.6 Analyzing Problems
3.7 Multiple Parameters
3.8 Space Bounds
3.9 Some Practical Considerations
3.10 Further Reading
3.11 Exercises
3.12 Projects
Part II fundamental Data Structures
Chapter 4 Lists,Stacks,and Queues
4.1 Lists
4.1.1 Array-Based List Implementation
4.1.2 Linked List
4.1.3 Comparison of List Implementations
4.1.4 Element Implementations
4.1.5 Doubly Linked List
4.1.6 Circular 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 Exercises
4.5 Projects
Chapter 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 Implementations
5.3.1 Pointer-Based Node Implementations
5.3.2 Space Requirements
5.3.3 Array Implementation for Complete Binary Trees
5.4 Huffman Coding Trees
5.4.1 Building Huffman Coding Trees
5.4.2 Assigning and Using Huffman Codes
5.5 Binary Search Trees
5.6 Heaps and Priority Queues
5.7 Further Reading
5.8 Exercises
5.9 Projects
Chapter 6 General 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
Chapter 7 Graphs
7.1 Terminology and Representations
7.2 Graph Implementations
7.3 Graph Traversals
7.3.1 Depth-First Search
7.3.2 Breadth-First Search
7.3.3 Topological Sort
7.4 Shortest-Paths Problems
7.4.1 Single-Source Shortest Paths
7.4.2 All-Pairs Shortes Paths
7.5 Minimum-Cost Spanning Trees
7.5.1 Prim's Algorithm
7.5.2 Kruskal;s Algorithm
7.6 Further Reading
7.7 Exercises
7.8 Projects
Part III Sorting and Searching
Chapter 8 Internal Sorting
8.1 sorting Terminology and Notation
8.2 Three Sorting Algorithms
8.2.1 Insertion Sort
8.2.2 Bubble Sort
8.2.3 Selection Sort
8.2.4 The Cost of Exchange Sorting
8.3 Shellsort
8.4 Quicksort
8.5 Mergesort
8.6 Heapsort
8.7 Binsort and Radix Sort
8.8 An Empirical Comparison of Sorting Algorithms
8.9 Lower Bounds for Sorting
8.10 Further Reading
8.11 Exercises
8.12 Projects
Chapter 9 File Processing and External Sorting
9.1 Primary Versus Secondary Storage
9.2 Disk and Tape Drives
9.2.1 Disk Access Costs
9.2.2 Magnetic Tape
9.3 Buffers and Buffer Pools
9.4 The Programmer's View of Files
9.5 External Sorting
9.6 Simple Approaches to External Sorting
9.7 Replacement Selection
9.8 Multiway Merging
9.9 Further Reading
9.10 Exercises
9.11 Projects
Chapter 10 Searching
10.1 Searching Sorted Arrays
10.2 Self-Organizing Lists
10.3 Searching in Sets
10.4 Hashing
10.4.1 Hash Functions
10.4.2 Open Hashing
10.4.3 Closed Hashing
10.5 Further Reading
10.6 Exercises
10.7 Projects
Chapter 11 Indexing
11.1 Linear Indexing
11.2 ISAM
11.3 Tree Indexing
11.4 2-3 Trees
11.5 B-Trees
11.5.1 B+-Trees
11.5.2 B-Tree Analysis
11.6 Further Reading
11.7 Exercises
11.8 Projects
Part IV Applications and Advanced Topics
Chapter 12 Lists and Arrays Revisited
12.1 Skip Lists
12.2 Multilists
12.3 Matrix Representations
12.4 Memory Management
12.4.1 Dynamic Storage Allocation
12.4.2 Failure Policies and Garbage Collection
12.5 Further Reading
12.6 Exercises
12.7 Projects
Chapter 13 Advanced Tree Structures
13.1 Tries
13.2 Splay Trees
13.3 Spatial Data Structures
13.3.1 The K-D Tree
13.3.2 The PR quadtree
13.3.3 Other Spatial Data Structures
13.4 Further Reading
13.5 Exercises
13.6 Projects
Chapter 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
Chapter 15 Limits to Computation
15.1 Introduction
15.2 Reductions
15.3 Hard Problems
15.3.1 NP-Completeness
15.3.2 Getting Around NP-Complete Problems
15.4 Impossible Problems
15.4.1 Uncountability
15.4.2 The Halting Problem is Unsolvable
15.4.3 Determining Program Behavior is Unsolvable
15.5 Further Reading
15.6 Exercises
15.7 Projects
Part V Appendix
Appendix A Java Tutorial for C and Pascal Programmers
A.1 Example 1：Interface for Lists
A.2 Example 2：Array-Based List Implementation
A.3 Example 3：Linked List Implementation
Bibliography
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