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Data Structure and Algorithm Analysis, Java Language Description, 2nd edition

Data structure and algorithm are almost necessary topics for IT Internet companies to interview. Although they may not be used much in the development process, they can reflect a programmer’s basic skills and logical thinking ability. However, most data structure and algorithm books are based on C language, this book uses Java language discussion, perfect to fill this gap. At any time the application function expands, the number of users is gradually increasing, people’s requirements for performance and algorithm analysis are also growing, this book is the best choice for Java programmers to learn data structure and algorithm, code farming books network recommended!

Directory: Chapter 1 Introduction 1.1 The content discussed in this book 1.2 Mathematical knowledge review 1.3 Recursion brief 1.4 Implement generic feature component pre-Java5 1.5 Implement generic feature component using Java5 generality 1.6 Function object Chapter 2 Algorithm analysis 2.1 Mathematical basis 2.2 Model 2.3 Issues to Analyze 2.4 Runtime Calculations Chapter 3 Tables, Stacks, and Queues 3.1 Abstract Data Types 3.2 Tables ADT 3.3 Tables in the Java Collections API 3.4 Implementation of the ArrayList class 3.5 Implementation of the Linked List class 3.6 Stack ADT 3.7 Queue ADT Chapter 4 Tree 4.1 Preparatory Knowledge 4.2 Binary Tree 4.3 Search tree ADT — Binary search tree 4.4 AVL tree 4.5 Stretch tree 4.6 Tree traversal 4.7 B tree 4.8 Sets and Mappings in the Standard Library Chapter 5 Hashing 5.1 General ideas 5.2 Hash function 5.3 Split Chingmethod 5.4 Hash without Linked list 5.5 Hash again 5.6 Hash in standard Library 5.7 Diffused Columns Chapter 6 Priority queue (heap) 6.1 Model 6.2 Some simple implementation 6.3 Binary heap 6.4 Priority queue applications 6.5 D-heap 6.6 Left Heap 6.7 Oblique Heap 6.8 Binomial Queue 6.9 Priority queue in the Standard Library Chapter 7 Sorting 7.1 Preliminary Knowledge 7.3 Lower bounds of some Simple sorting algorithms 7.4 Hill Sort 7.5 Heap sort 7.6 Merge Sort 7.7 Quicksort 7.8 General lower bounds of sorting algorithms 7.9 Bucket sorting 7.10 External Sorting Chapter 8 Incongruence classes 8.1 Equivalence relations 8.2 Dynamic equivalence problems 8.3 Basic data structures 8.4 Agile Union algorithms 8.5 Path compression 8.6 Worst Case of Path compression and rank Union 8.7 An application Chapter 9 Graph Theory Algorithm 9.1 Several Definitions 9.2 Topology Sorting 9.3 Shortest Path Algorithm 9.4 Network Traffic problems 9.5 Minimum spanning tree 9.6 Depth-first Search applications 9.7 NP complete Introduction Chapter 10 Algorithm design techniques 10.1 Greedy algorithm 10.2 Didivide and conquer Algorithm 10.3 Dynamic programming 10.4 Randomization Algorithm 10.5 Backtracking Algorithm Chapter 11 Amortized Analysis 11.1 An irrelevant intelligence problem 11.2 Binomial queue 11.3 Inclined Heap 11.4 Fibonacci Heap 11.5 Stretch tree Chapter 12 Advanced Data Structures and their implementation 12.1 Top-down stretch tree 12.2 Red-Black Tree 12.3 Deterministic skip table 12.4 AA Tree 12.5 TreAP Tree 12.6 K-D tree 12.7 Paired Heap

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