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Symbolic Model Checking of Stochastic Systems: Theory and Implementation
Author(s) -
M. Küntz,
Markus Siegle
Publication year - 2006
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-33102-6
DOI - 10.1007/11691617_6
Subject(s) - computer science , model checking , automaton , temporal logic , theoretical computer science , semantics (computer science) , markov chain , modal logic , algorithm , stochastic petri net , computation tree logic , programming language , modal , petri net , chemistry , machine learning , polymer chemistry
This paper presents IM-SPDL, a stochastic extension of the modal logic PDL, which supports the specification of complex performance and dependability requirements. The logic is interpreted over extended stochastic labelled transition systems (ESLTS), i.e. transition systems containing both immediate and Markovian transitions. We define the syntax and semantics of the new logic and show that IM-SPDL provides powerful means to specify path-based properties with timing restrictions. In general, paths can be characterised by regular expressions, also called programs, where the executability of a program may depend on the validity of test formulae. For the model checking of IM-SPDL time-bounded path formulae, a deterministic program automaton is constructed from the requirement. Afterwards the product transition system between this automaton and the ESLTS is built and subsequently transformed into a continuous time Markov Chain (CTMC) on which numerical analysis is performed. Empirical results given in the paper show that model checking IM-SPDL can be realised efficiently in practice

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