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Data Structures and Algorithm Analysis in C++, 3rd Edition
- By Mark A. Weiss
- Published Feb 28, 2006 by Pearson.
Book
- Sorry, this book is no longer in print.
About
Features
- Discussion of algorithm and design techniques covers greedy algorithms, divide and conquer algorithms, dynamic programming, randomized algorithms, and backtracking.
- Covers topics and data structures such as Fibonacci heaps, skew heaps, binomial queue, skip lists and splay trees.
- A full chapter on amortized analysis examines the advanced data structures presented earlier in the book.
- Chapter on advanced data structures and their implementation covers red black trees, top down splay trees, treaps, k-d trees, pairing heaps, and more.
- End-of-chapter exercises, ranked by difficulty, reinforce the material from the chapter while providing readers an opportunity to put those concepts into practice.
- All code has been updated and tested on multiple platforms and conforms to the ISO standard.
Description
- Copyright 2007
- Edition: 3rd
- Book
- ISBN-10: 0-321-44146-X
- ISBN-13: 978-0-321-44146-1
Advanced Data Structures/Algorithms C++
Data Structures and Algorithm Analysis in C++, 3/e
Mark Allen Weiss, Florida International University
ISBN : 0-321-37531-9
Mark Allen Weiss teaches readers to reduce time constraints and develop programs efficiently by analyzing an algorithm’s feasibility before it is coded. His innovative approach to advanced algorithms and data structures simultaneously develops sound algorithm analysis and programming skills.
The Third Edition features a full C++ language update and incorporation of the Standard Template Library. There is new treatment of lists, stacks, queues, and trees, and an entire chapter dedicated to amortized analysis and advanced data structures such as the Fibonacci heap.
Highlights of the Third Edition
• All code has been updated and tested to ensure compliance with the ANSI/ISO C++ standards
• Standard Template Library fully incorporated throughout the text
• Completely revised coverage of lists, stacks, and queues in Chapter 3
• Readability enhanced by fresh interior design with new figures and examples
• End-of-chapter exercises, ranked by difficulty, reinforce key chapter concepts
Visit aw.com/computing for more information about Addison-Wesley computing books. Sample Content
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 C++ Classes
1.5 C++ Details
1.6 Templates
1.7 Using Matrices
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 vector and list in the STL
3.4 Implementation of vector
3.5 Implementation of list
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
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 Indirect Sorting
7.9 A General Lower Bound for Sorting
7.10 Bucket Sort
7.11 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
Appendix A - Separate Compilation Of Class Templates