A Compositional Semantics for Repairable BDMPs

Khan, Shahid; Katoen, Joost-Pieter; Bouissou, Marc

doi:10.1007/978-3-030-54549-9_6

Cited by 5 publications

(2 citation statements)

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“…While the general definition of BDMPs in [9] allows the use of arbitrary Markov processes for defining basic events, we restrict ourselves to the commonly used exponential distributions. The semantics of BDMPs has been translated into Markov automaton in [26], and generalised stochastic Petri nets in [27]. The underlying stochastic process of a BDMP is a continuous-time Markov chain (CTMC).…”

Section: Fig 1 Lazy Verification For Reliabilitymentioning

confidence: 99%

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Scalable Reliability Analysis by Lazy Verification

Khan

Katoen

Volk

et al. 2021

Lecture Notes in Computer Science

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This paper presents an iterative method to analyse system reliability models. The key idea is to analyse a partial state space of a reliability model in a conservative and an optimistic manner. By considering unexplored states as being always operational or, dually, already failed, our analysis yields sound upper-and lower-bounds on the system's reliability. This approach is applied in an iterative manner until the desired precision is obtained. We present details of our approach for Booleanlogic driven Markov processes (BDMPs), an expressive fault tree variant intensively used in analysing energy systems. Based on a prototypical implementation on top of the probabilistic model checker Storm, we experimentally compare our technique to two alternative BDMP analysis techniques: discrete-event simulation obtaining statistical bounds, and a recent closed-form technique for obtaining pessimistic system lifetimes. Our experiments show that mostly only a fragment of the state space needs to be investigated enabling the reliability analysis of models that could not be handled before.S. Khan-supported by a HEC-DAAD scholarship. 1 Known as confidence intervals.

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Section: Fig 1 Lazy Verification For Reliabilitymentioning

confidence: 99%

“…The (compositional) semantics of BDMPs in terms of CTMCs is fully explained in [26,27]. We present the general idea by an example.…”

Section: State-space Generationmentioning

confidence: 99%