Data Structures and Algorithm Analysis in Java

As the speed and power of computers increases, so does the need for effective programming and algorithm analysis. By approaching these skills in tandem, Mark Allen Weiss teaches readers to develop well-constructed, maximally efficient programs in Java. A full language update to Java 5.0 throughout the text--particularly its use of generics--adds immeasurable value to this advanced study of data structures and algorithms. This Second Edition features integrated coverage of the Java Collections Library as well as a complete revision of lists, stacks, queues, and trees. Weiss clearly explains topics from binary heaps to sorting to NP-completeness, and dedicates a full chapter to amortized analysis and advanced data structures and their implementation. Figures and examples illustrating successive stages of algorithms contribute to Weiss' careful, rigorous and in-depth analysis of each type of algorithm. A logical organization of topics and full access to source code compliment the text's coverage.

ISBN 0321373197   Pages 576 ISBN13 9780321373199 (What's this?)   Weight (grammes) 842 Publisher Pearson Education (US)   Published in Upper Saddle River Imprint Pearson Education (US)   Previous ISBN 9780201357547 Format Paperback   Height (mm) 235 Publication date 01 Oct 2005   Width (mm) 191 DEWEY 005.133   Academic level Professional / Scholarly DEWEY edition DC22

Chapter 1 Introduction 1.1 What's the Book About? 1.2 Mathematics Review 1.3 A Brief Introduction to Recursion 1.4 Implementing Generic Components Pre Java 5 1.5 Implementing Generic Components Using Java 5 Generics 1.6 Function Objects Chapter 2 Algorithm Analysis 2.1 Mathematical Background 2.2 Model 2.3 What to Analyze 2.4 Running Time Calculations Chapter 3 Lists, Stacks, and Queues 3.1 Abstract Data Types (ADTs) 3.2 The List ADT 3.3 Lists in the Java Collections API 3.4 Implementation of ArrayList 3.5 Implementation of LinkedList 3.6 The Stack ADT 3.7 The Queue ADT Chapter 4 Trees 4.1 Preliminaries 4.2 Binary Trees 4.3 The Search Tree ADT--Binary Search Trees 4.4 AVL Trees 4.5 Splay Trees 4.6 Tree Traversals (Revisited) 4.7 B-Trees 4.8 Sets and Maps in the Standard Library 4.9 Summary Chapter 5 Hashing 5.1 General Idea 5.2 Hash Function 5.3 Separate Chaining 5.4 Hash Tables Without Linked Lists 5.5 Rehashing 5.6 Hash Tables in the Standard Library 5.7 Extendible Hashing Chapter 6 Priority Queues (Heaps) 6.1 Model 6.2 Simple Implementations 6.3 Binary Heap 6.4 Applications of Priority Queues 6.5 d-Heaps 6.6 Leftist Heaps 6.7 Skew Heaps 6.8 Binomial Queues 6.9 Priority Queues in the Standard Library Chapter 7 Sorting 7.1 Preliminaries 7.2 Insertion Sort 7.3 A Lower Bound for Simple Sorting Algorithms 7.4 Shellsort 7.5 Heapsort 7.6 Mergesort 7.7 Quicksort 7.8 A General Lower Bound for Sorting 7.9 Bucket Sort 7.10 External Sorting Chapter 8 The Disjoint Set Class 8.1 Equivalence Relations 8.2 The Dynamic Equivalence Problem 8.3 Basic Data Structure 8.4 Smart Union Algorithms 8.5 Path Compression 8.6 Worst Case for Union-by-Rank and Path Compression 8.7 An Application Chapter 9 Graph Algorithms 9.1 Definitions 9.2 Topological Sort 9.3 Shortest-Path Algorithms 9.4 Network Flow Problems 9.5 Minimum Spanning Tree 9.6 Applications of Depth-First Search 9.7 Introduction to NP-Completeness Chapter 10 Algorithm Design Techniques 10.1 Greedy Algorithms 10.2 Divide and Conquer 10.3 Dynamic Programming 10.4 Randomized Algorithms 10.5 Backtracking Algorithms Chapter 11 Amortized Analysis 11.1 An Unrelated Puzzle 11.2 Binomial Queues 11.3 Skew Heaps 11.4 Fibonacci Heaps 11.5 Splay Trees Chapter 12 Advanced Data Structures and Implementation 12.1 Top-Down Splay Trees 12.2 Red-Black Trees 12.3 Deterministic Skip Lists 12.4 AA-Trees 12.5 Treaps 12.6 k-d Trees 12.7 Pairing Heaps

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