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Supporting Backward Transitions within Markov Chains when Modeling Complex User Behavior in the Palladio Component Model

dc.contributor.authorBarnert, Maximilian
dc.contributor.authorKrcmar, Helmut
dc.contributor.editorKelter, Udo
dc.date.accessioned2022-11-24T10:42:09Z
dc.date.available2022-11-24T10:42:09Z
dc.date.issued2020
dc.description.abstractThe specification of complex user behavior as accurate as possible is required in order to evaluate performance characteristics for application systems. Approaches exist to model probabilistic aspects within user behavior for session-based application systems using Markov chains. To integrate these approach into performance prediction activities, the authors transform the workload specifications of WESSBAS into performance model instances of the Palladio Component Model (PCM). This paper presents our approach to enable backward transitions within Markov chains using available elements of the PCM meta-model. By extending the existing approach, further complexity within workload for application systems is supported during performance modeling.en
dc.identifier.pissn0720-8928
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39800
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftwaretechnik-Trends Band 40, Heft 3
dc.relation.ispartofseriesSoftwaretechnik-Trends
dc.subjectperformance
dc.subjectprediction
dc.subjectprobabilistic
dc.subjectMarkov
dc.subjectPalladio Component Model
dc.titleSupporting Backward Transitions within Markov Chains when Modeling Complex User Behavior in the Palladio Component Modelen
dc.typeText/Conference Paper
gi.citation.endPage24
gi.citation.publisherPlaceBonn
gi.citation.startPage22
gi.conference.date44147
gi.conference.locationLeipzig
gi.conference.sessiontitleSymposium on Software Performance (SSP)

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