Modelling, Reduction and Analysis of Markov Automata (extended version)

Dennis Guck, Hassan Hatefi, H. Hermanns, Joost P. Katoen, Mark Timmer

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    Abstract

    Markov automata (MA) constitute an expressive continuous-time compositional modelling formalism. They appear as semantic backbones for engineering frameworks including dynamic fault trees, Generalised Stochastic Petri Nets, and AADL. Their expressive power has thus far precluded them from effective analysis by probabilistic (and statistical) model checkers, stochastic game solvers, or analysis tools for Petri net-like formalisms. This paper presents the foundations and underlying algorithms for efficient MA modelling, reduction using static analysis, and most importantly, quantitative analysis. We also discuss implementation pragmatics of supporting tools and present several case studies demonstrating feasibility and usability of MA in practice.
    Original languageUndefined
    Place of PublicationIthaca, NY, USA
    PublisherCornell University
    Number of pages27
    Publication statusPublished - 30 May 2013

    Publication series

    Name
    PublisherCornell University
    No.arXiv:1305.7050

    Keywords

    • EC Grant Agreement nr.: FP7/2007-2013
    • IR-86179
    • EC Grant Agreement nr.: FP7/318490
    • Continuous time
    • Process Algebra
    • Markov Automata
    • EC Grant Agreement nr.: FP7/257005
    • Quantitative analysis
    • EC Grant Agreement nr.: FP7/295261
    • METIS-297670
    • EWI-23394

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