04133nam 22007695 450 99646620570331620230221232019.03-642-14866-210.1007/978-3-642-14866-8(CKB)2670000000036361(SSID)ssj0000446283(PQKBManifestationID)11296935(PQKBTitleCode)TC0000446283(PQKBWorkID)10490925(PQKB)11518751(DE-He213)978-3-642-14866-8(MiAaPQ)EBC3065577(PPN)149018509(EXLCZ)99267000000003636120100729d2010 u| 0engurnn|008mamaatxtccrAlgorithm Engineering[electronic resource] Bridging the Gap Between Algorithm Theory and Practice /edited by Matthias Müller-Hannemann, Stefan Schirra1st ed. 2010.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2010.1 online resource (XVI, 513 p. 72 illus.) Theoretical Computer Science and General Issues,2512-2029 ;5971Bibliographic Level Mode of Issuance: Monograph3-642-14865-4 Includes bibliographical references (p. [454]-496) and index.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.Theoretical Computer Science and General Issues,2512-2029 ;5971Computer programmingAlgorithmsMachine theorySoftware engineeringComputer simulationArtificial intelligence—Data processingProgramming TechniquesAlgorithmsFormal Languages and Automata TheorySoftware EngineeringComputer ModellingData ScienceComputer programming.Algorithms.Machine theory.Software engineering.Computer simulation.Artificial intelligence—Data processing.Programming Techniques.Algorithms.Formal Languages and Automata Theory.Software Engineering.Computer Modelling.Data Science.004.01/5181Müller-Hannemann Matthiasedthttp://id.loc.gov/vocabulary/relators/edtSchirra Stefanedthttp://id.loc.gov/vocabulary/relators/edtBOOK996466205703316Algorithm engineering1980326UNISA