Synopses & Reviews
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.
Synopsis
Advanced Data Structures/Algorithms Java Data Analysis and Algorithm Analysis in Java, 2/e Mark Allen Weiss, "Florida International University"
Synopsis
In this text, readers are able to look at specific problems and see how careful implementations can reduce the time constraint for large amounts of data from several years to less than a second. This new edition contains all the enhancements of the new Java 5.0 code including detailed examples and an implementation of a large subset of the Java 5.0 Collections API. This text is for readers who want to learn good programming and algorithm analysis skills simultaneously so that they can develop such programs with the maximum amount of efficiency. Readers should have some knowledge of intermediate programming, including topics as object-based programming and recursion, and some background in discrete math.
Table of Contents
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