OpenDSA: Open Source Interactive Data Structures and Algorithms
Collection of materials to support courses in a wide variety of Computer Science-related topics such as Data Structures and Algorithms (DSA), Formal Languages, Finite Automata, and Programming Languages. Includes many interactive exercises.
Tag(s): Algorithms and Data Structures
Publication date: 17 Mar 2016
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Views: 7,561
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Post time: 23 Apr 2016 12:00:00
OpenDSA: Open Source Interactive Data Structures and Algorithms
Clifford A. Shaffer wrote:Welcome to the homepage for the OpenDSA Active-eBook Project. We have created infrastructure and materials to support courses in a wide variety of Computer Science-reltated topics such as Data Structures and Algorithms (DSA), Formal Languages, Finite Automata, and Programming Languages.
OpenDSA materials include many visualizations and interactive exercises. Our primary philosophy is that students learn this material best when they engage them material and then practice it until they have demonstrated their proficiency. This page shows a sampling of screenshots (and if you click on a screenshot, you will be taken to the actual artifact). In the same way, a given visualization or exercise could be incorporated individually into an instructor's own web pages.
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).
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).