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001 978-3-540-36383-5
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008 121227s2002 gw | s |||| 0|eng d
020 _a9783540363835
_9978-3-540-36383-5
024 7 _a10.1007/3-540-36383-1
_2doi
050 4 _aQA75.5-76.95
072 7 _aUY
_2bicssc
072 7 _aCOM000000
_2bisacsh
072 7 _aUY
_2thema
082 0 4 _a004
_223
245 1 0 _aExperimental Algorithmics
_h[electronic resource] :
_bFrom Algorithm Design to Robust and Efficient Software /
_cedited by Rudolf Fleischer, Bernhard Moret, Erik Meineche Schmidt.
250 _a1st ed. 2002.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2002.
300 _aXVIII, 286 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v2547
505 0 _aAlgorithm 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.
520 _a 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.
650 0 _aComputer science.
650 0 _aArtificial intelligence
_xData processing.
650 0 _aAlgorithms.
650 0 _aNumerical analysis.
650 0 _aComputer science
_xMathematics.
650 0 _aDiscrete mathematics.
650 1 4 _aComputer Science.
650 2 4 _aData Science.
650 2 4 _aAlgorithms.
650 2 4 _aNumerical Analysis.
650 2 4 _aDiscrete Mathematics in Computer Science.
700 1 _aFleischer, Rudolf.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aMoret, Bernhard.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aMeineche Schmidt, Erik.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540003465
776 0 8 _iPrinted edition:
_z9783662177303
830 0 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v2547
856 4 0 _uhttps://doi.org/10.1007/3-540-36383-1
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
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942 _cSPRINGER
999 _c188192
_d188192