Data Structures and Algorithm Analysis in Java

Advanced Data Structures/Algorithms Java

Data Analysis and Algorithm Analysis in Java, 2/e

Mark Allen Weiss, Florida International University

ISBN : 0-321-37013-9

As the speed and power of computers increase, so does the need for effective programming and algorithm analysis. Mark Allen Weiss approaches these skills jointly to teach the development of well-constructed, maximally efficient programs in Java.

Readers benefit from the full language update to Java 5.0, including generics, and the integrated coverage of the Java Collections Library in this advanced study of data structures and algorithms. Weiss clearly explains his careful, rigorous and in-depth analysis of each type of algorithm.

This Second Edition features:

• Full integration of the new Java 5.0 programming language and the Java Collections Library

• Enhanced interior design, with figures and examples illustrating successive stages of algorithms

• Completely revised coverage of lists, stacks, and queues in Chapter 3

• Full chapter dedicated to the implementation of amortized analysis and advanced data structures

• End-of-chapter exercises, ranked by difficulty, reinforce key chapter concepts

 Visit aw.com/computing for more information about Addison-Wesley computing books.

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