Data Structures and Algorithms in Java, 5th Edition

by Michael T. Goodrich (University of California at Irvine); Roberto Tamassia (Brown Univ.)

• ISBN13: 9780470383261
• ISBN10: 0470383267
• Edition: 5th
• Format: Hardcover
• Copyright: 2010-02-01
• Publisher: Wiley

Summary

This newest edition examines fundamental data structures by following a consistent object-oriented framework that builds intuition and analysis skills of data structures and algorithms Presents new figures, simpler language, and more practical motivations from real-world scenarios Numerous illustrations, Web-based animations, and simplified mathematical analyses help readers quickly learn important concepts

Author Biography

Professors Goodrich and Tamassia are well-recognized researchers in data structures and algorithms. Michael Goodrich received his Ph.D. in Computer Science from Purdue University. He is currently a professor in the Department of Computer Science at the University of California, Irvine. Roberto Tamassia received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign. He is currently a professor in the Department Science at Brown University. Both professors are winners of numerous teaching awards for their teaching of data structures and algorithms.

Table of Contents

Java Primer

Getting Started: Classes, Types, and Objects

Methods

Expressions

Control Flow

Arrays

Simple Input and Output

An Example Program

Nested Classes and Packages

Writing a Java Program

Exercises

Object-Oriented Design

Goals, Principles, and Patterns

Inheritance and Polymorphism

Exceptions

Interfaces and Abstract Classes

Casting and Generics

Exercises

Indices, Nodes, and Recursion

Using Arrays

Singly Linked Lists

Doubly Linked Lists

Circularly Linked Lists and Linked-List Sorting

Recursion

Exercises

Analysis Tools

The Seven Functions Used in This Book

Analysis of Algorithms

Simple Justification Techniques

Exercises

Stacks, Queues, and Deques

Stacks

Queues

Double-Ended Queues

Exercises

List and Iterator ADTs

Array Lists

Node Lists

Iterators

List ADTs and the Collections Framework

Case Study: The Move-to-Front Heuristic

Exercises

Trees

General Trees

Tree Traversal Algorithms

Binary Trees

Exercises

Heaps and Priority Queues

The Priority Queue Abstract Data Type

Implementing a Priority Queue with a List

Heaps

Adaptable Priority Queues

Exercises

Hash Tables, Maps, and Skip Lists

Maps

Hash Tables

Ordered Maps

Skip Lists

Dictionaries

Exercises

Search Trees

Binary Search Trees

AVL Trees

Splay Trees

(2,4) Trees

Red-Black Trees

Exercises

Sorting, Sets, and Selection

Merge-Sort

Quick-Sort

Studying Sorting through an Algorithmic Lens

Sets and Union/Find Structures

Selection

Exercises

Strings and Dynamic Programming

String Operations

Dynamic Programming

Pattern Matching Algorithms

Text Compression and the Greedy Method

Tries

Exercises

Graph Algorithms

Graphs

Data Structures for Graphs

Graph Traversals

Directed Graphs

Shortest Paths

Minimum Spanning Trees

Exercises

Memory Management and B-Trees

Memory Management

External Memory and Caching

External Searching and B-Trees

External-Memory Sorting

Exercises

A Useful Mathematical Facts

Bibliography

Index

Table of Contents provided by Publisher. All Rights Reserved.