Data Structures & Algorithm Analysis in Java (Edition 3.2)

This text helps readers understand how to select or design the tools that will best solve specific problems, focusing on creating efficient data structures and algorithms. It uses Java as the programming language.

**Tag(s):**
Algorithms and Data Structures
Java

**Publication date**: 28 Mar 2013

**ISBN-10**:
0486485811

**ISBN-13**:
9780486485812

**Paperback**:
601 pages

**Views**: 6,170

Data Structures & Algorithm Analysis in Java (Edition 3.2)

This text helps readers understand how to select or design the tools that will best solve specific problems, focusing on creating efficient data structures and algorithms. It uses Java as the programming language.

From the Book Description:

With its focus on creating efficient data structures and algorithms, this comprehensive text helps readers understand how to select or design the tools that will best solve specific problems. It uses Java as the programming language and is suitable for second-year data structure courses and computer science courses in algorithm analysis.

Techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium. The text also explores tradeoff issues, familiarizes readers with the most commonly used data structures and their algorithms, and discusses matching appropriate data structures to applications. The author offers explicit coverage of design patterns encountered in the course of programming the book's basic data structures and algorithms. Numerous examples appear throughout the text.

With its focus on creating efficient data structures and algorithms, this comprehensive text helps readers understand how to select or design the tools that will best solve specific problems. It uses Java as the programming language and is suitable for second-year data structure courses and computer science courses in algorithm analysis.

Techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium. The text also explores tradeoff issues, familiarizes readers with the most commonly used data structures and their algorithms, and discusses matching appropriate data structures to applications. The author offers explicit coverage of design patterns encountered in the course of programming the book's basic data structures and algorithms. Numerous examples appear throughout the text.

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About The Author(s)

Cliff Shaffer is Professor of Computer Science at Virginia Tech, where he has been since 1987. He received his PhD from University of Maryland in 1986. Over his career, Dr. Shaffer's research efforts have spanned three major themes: Data structures and algorithms for spatial applications, integrated problem-solving environments for engineering and science applications (most notably for systems biology), and simulation and visualization for education (including Computer Science, Statistics, and Geography).

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