Data Structures and Algorithm Analysis in C++, 3rd Edition

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