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.
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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