04599nam 22007935 450 991014388940332120200706032105.03-540-36383-110.1007/3-540-36383-1(CKB)1000000000211884(SSID)ssj0000323041(PQKBManifestationID)11272565(PQKBTitleCode)TC0000323041(PQKBWorkID)10296389(PQKB)10211577(DE-He213)978-3-540-36383-5(MiAaPQ)EBC3072643(PPN)15521845X(EXLCZ)99100000000021188420121227d2002 u| 0engurnn#008mamaatxtccrExperimental Algorithmics From Algorithm Design to Robust and Efficient Software /edited by Rudolf Fleischer, Bernhard Moret, Erik Meineche Schmidt1st ed. 2002.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2002.1 online resource (XVIII, 286 p.)Lecture Notes in Computer Science,0302-9743 ;2547Bibliographic Level Mode of Issuance: Monograph3-540-00346-0 Includes bibliographical references at the end of each chapters and index.Algorithm Engineering for Parallel Computation -- Visualization in Algorithm Engineering: Tools and Techniques -- Parameterized Complexity: The Main Ideas and Connections to Practical Computing -- A Comparison of Cache Aware and Cache Oblivious Static Search Trees Using Program Instrumentation -- Using Finite Experiments to Study Asymptotic Performance -- WWW.BDD-Portal.ORG: An Experimentation Platform for Binary Decision Diagram Algorithms -- Algorithms and Heuristics in VLSI Design -- Reconstructing Optimal Phylogenetic Trees: A Challenge in Experimental Algorithmics -- Presenting Data from Experiments in Algorithmics -- Distributed Algorithm Engineering -- Implementations and Experimental Studies of Dynamic Graph Algorithms. Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications. Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.Lecture Notes in Computer Science,0302-9743 ;2547Computer scienceData structures (Computer science)AlgorithmsNumerical analysisComputer science—MathematicsComputer Science, generalhttps://scigraph.springernature.com/ontologies/product-market-codes/I00001Data Structureshttps://scigraph.springernature.com/ontologies/product-market-codes/I15017Algorithm Analysis and Problem Complexityhttps://scigraph.springernature.com/ontologies/product-market-codes/I16021Numeric Computinghttps://scigraph.springernature.com/ontologies/product-market-codes/I1701XDiscrete Mathematics in Computer Sciencehttps://scigraph.springernature.com/ontologies/product-market-codes/I17028Algorithmshttps://scigraph.springernature.com/ontologies/product-market-codes/M14018Computer science.Data structures (Computer science).Algorithms.Numerical analysis.Computer science—Mathematics.Computer Science, general.Data Structures.Algorithm Analysis and Problem Complexity.Numeric Computing.Discrete Mathematics in Computer Science.Algorithms.005.1Fleischer Rudolfedthttp://id.loc.gov/vocabulary/relators/edtMoret Bernhardedthttp://id.loc.gov/vocabulary/relators/edtMeineche Schmidt Erikedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910143889403321Experimental algorithmics953833UNINA