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001 978-3-642-14866-8
003 DE-He213
005 20240730201445.0
007 cr nn 008mamaa
008 100729s2010 gw | s |||| 0|eng d
020 _a9783642148668
_9978-3-642-14866-8
024 7 _a10.1007/978-3-642-14866-8
_2doi
050 4 _aQA76.6-76.66
072 7 _aUM
_2bicssc
072 7 _aCOM051000
_2bisacsh
072 7 _aUM
_2thema
082 0 4 _a005.11
_223
245 1 0 _aAlgorithm Engineering
_h[electronic resource] :
_bBridging the Gap Between Algorithm Theory and Practice /
_cedited by Matthias Müller-Hannemann, Stefan Schirra.
250 _a1st ed. 2010.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2010.
300 _aXVI, 513 p. 72 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v5971
505 0 _a1. 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.
520 _aAlgorithms 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.
650 0 _aComputer programming.
_94169
650 0 _aAlgorithms.
_93390
650 0 _aMachine theory.
_9167254
650 0 _aSoftware engineering.
_94138
650 0 _aComputer simulation.
_95106
650 0 _aArtificial intelligence
_xData processing.
_921787
650 1 4 _aProgramming Techniques.
_9167255
650 2 4 _aAlgorithms.
_93390
650 2 4 _aFormal Languages and Automata Theory.
_9167256
650 2 4 _aSoftware Engineering.
_94138
650 2 4 _aComputer Modelling.
_9167257
650 2 4 _aData Science.
_934092
700 1 _aMüller-Hannemann, Matthias.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9167258
700 1 _aSchirra, Stefan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9167259
710 2 _aSpringerLink (Online service)
_9167260
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783642148651
776 0 8 _iPrinted edition:
_z9783642148675
830 0 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v5971
_9167261
856 4 0 _uhttps://doi.org/10.1007/978-3-642-14866-8
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
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999 _c96542
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