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OverviewAlgorithms 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. Full Product DetailsAuthor: Matthias Müller-Hannemann , Stefan SchirraPublisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K Volume: 5971 Dimensions: Width: 15.50cm , Height: 2.70cm , Length: 23.50cm Weight: 0.807kg ISBN: 9783642148651ISBN 10: 3642148654 Pages: 513 Publication Date: 05 August 2010 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1. 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.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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