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020 _a9783540446675
_9978-3-540-44667-5
024 7 _a10.1007/3-540-44667-2
_2doi
050 4 _aQA76.758
072 7 _aUMZ
_2bicssc
072 7 _aCOM051230
_2bisacsh
072 7 _aUMZ
_2thema
082 0 4 _a005.1
_223
245 1 0 _aLectures on Formal Methods and Performance Analysis
_h[electronic resource] :
_bFirst EEF/Euro Summer School on Trends in Computer Science Berg en Dal, The Netherlands, July 3-7, 2000. Revised Lectures /
_cedited by Ed Brinksma, Holger Hermanns, Joost-Pieter Katoen.
250 _a1st ed. 2001.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2001.
300 _aVII, 434 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 ;
_v2090
505 0 _aFormal Methods for Performance Evaluation -- Markovian Models for Performance and Dependability Evaluation -- to Stochastic Petri Nets -- Non-Markovian Analysis -- Process Algebra and Markov Chains -- Verification of Randomized Distributed Algorithms -- Constructing Automata from Temporal Logic Formulas: A Tutorial? -- Exploiting Structure in Solution: Decomposing Compositional Models -- Stochastic Activity Networks: Formal Definitions and Concepts? -- Distributed and Structured Analysis Approaches to Study Large and Complex Systems? -- General Distributions in Process Algebra.
520 _aTraditionally, models and methods for the analysis of the functional correctness of reactive systems, and those for the analysis of their performance (and - pendability) aspects, have been studied by di?erent research communities. This has resulted in the development of successful, but distinct and largely unrelated modeling and analysis techniques for both domains. In many modern systems, however, the di?erence between their functional features and their performance properties has become blurred, as relevant functionalities become inextricably linked to performance aspects, e.g. isochronous data transfer for live video tra- mission. During the last decade, this trend has motivated an increased interest in c- bining insights and results from the ?eld of formal methods – traditionally - cused on functionality – with techniques for performance modeling and analysis. Prominent examples of this cross-fertilization are extensions of process algebra and Petri nets that allow for the automatic generation of performance models, the use of formal proof techniques to assess the correctness of randomized - gorithms, and extensions of model checking techniques to analyze performance requirements automatically. We believe that these developments markthe - ginning of a new paradigm for the modeling and analysis of systems in which qualitative and quantitative aspects are studied from an integrated perspective. We are convinced that the further worktowards the realization of this goal will be a growing source of inspiration and progress for both communities.
650 0 _aSoftware engineering.
650 0 _aComputer engineering.
650 0 _aComputer networks .
650 0 _aComputer science.
650 0 _aElectronic digital computers
_xEvaluation.
650 1 4 _aSoftware Engineering.
650 2 4 _aComputer Engineering and Networks.
650 2 4 _aComputer Science Logic and Foundations of Programming.
650 2 4 _aSystem Performance and Evaluation.
650 2 4 _aComputer Communication Networks.
700 1 _aBrinksma, Ed.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aHermanns, Holger.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKatoen, Joost-Pieter.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540424796
776 0 8 _iPrinted edition:
_z9783662181171
830 0 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v2090
856 4 0 _uhttps://doi.org/10.1007/3-540-44667-2
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