Taming confusion for modeling and implementing probabilistic concurrent systems
ESOP'13 Proceedings of the 22nd European conference on Programming Languages and Systems
PETRI NETS'13 Proceedings of the 34th international conference on Application and Theory of Petri Nets and Concurrency
Confluence reduction for markov automata
FORMATS'13 Proceedings of the 11th international conference on Formal Modeling and Analysis of Timed Systems
Modelling, reduction and analysis of markov automata
QEST'13 Proceedings of the 10th international conference on Quantitative Evaluation of Systems
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This paper considers interactive Markov chains (IMCs), a natural generalization of transition systems and continuous-time Markov chains (CTMCs). We show how they can be used to provide a truly simple semantics of Generalized Stochastic Petri Nets (GSPNs). In fact, any GSPN. In particular, no restrictions are imposed on the concurrent/conflicting enabledness of immediate transitions. This contrasts with classical solutions for GSPNs which use weights. (A simple extension of IMCs also covers weights.) In addition, we will present novel analysis algorithms for expected time and long-run average time objectives of IMCs, i.e., GSPNs. Two case studies indicate the feasibility of these analyses and show that a classical reliability analysis for confused GSPNs may lead to significant over-estimations of the true probabilities. The key message is: nondeterminism is not a threat, treat it as is! This yields both a simple GSPN semantics and trustworthy analysis results.