Algorithm Engineering: Bridging the Gap between Algorithm Theory and Practice

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Authors and Corporations:	Müller-Hannemann, Matthias (Author), Schirra, Stefan (Other)
Title:	Algorithm Engineering: Bridging the Gap between Algorithm Theory and Practice/ edited by Matthias Müller-Hannemann, Stefan Schirra
Type of Resource:	E-Book
Language:	English
published:	Berlin, Heidelberg Springer Berlin Heidelberg 2010
Series:	SpringerLink Lecture notes in computer science ; 5971
Subjects:	Computer science Data structures (Computer science) Computer software Electronic data processing Computer Science Software engineering Computer simulation Machine theory. Computer programming. Algorithms. Artificial intelligence Aufsatzsammlung
Buchausg. u.d.T.:	Algorithm engineering, Berlin : Springer, 2010, XVI, 513 S.
Source:	Verbunddaten SWB
Access Information:	Elektronischer Volltext - Campuslizenz

Description
Abstract:	1. Foundations of Algorithm Engineering -- 2. Modeling -- 3. Selected Design Issues -- 4. Analysis of Algorithms -- 5. Realistic Computer Models -- 6. Implementation Aspects -- 7. Libraries -- 8. Experiments -- 9. Case Studies -- 10. Challenges in Algorithm Engineering. Algorithms are essential building blocks of computer applications. However, advancements in computer hardware, which render traditional computer models more and more unrealistic, and an ever increasing demand for efficient solution to actual real world problems have led to a rising gap between classical algorithm theory and algorithmics in practice. The emerging discipline of Algorithm Engineering aims at bridging this gap. Driven by concrete applications, Algorithm Engineering complements theory by the benefits of experimentation and puts equal emphasis on all aspects arising during a cyclic solution process ranging from realistic modeling, design, analysis, robust and efficient implementations to careful experiments. This tutorial - outcome of a GI-Dagstuhl Seminar held in Dagstuhl Castle in September 2006 - covers the essential aspects of this process in ten chapters on basic ideas, modeling and design issues, analysis of algorithms, realistic computer models, implementation aspects and algorithmic software libraries, selected case studies, as well as challenges in Algorithm Engineering. Both researchers and practitioners in the field will find it useful as a state-of-the-art survey.
Physical Description:	Online-Ressource (XVI, 513 p. 72 illus, digital)
ISBN:	9783642148668
DOI:	10.1007/978-3-642-14866-8