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Statistical Model Checking
, 2012
"... Abstract. Statistical modelchecking is an alternative verification technique applied on stochastic systems whose size is beyond numerical analysis ability. Given a model (most often a Markov chain) and a formula, it provides a confidence interval for the probability that the model satisfies the for ..."
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Abstract. Statistical modelchecking is an alternative verification technique applied on stochastic systems whose size is beyond numerical analysis ability. Given a model (most often a Markov chain) and a formula, it provides a confidence interval for the probability that the model satisfies
Statistical model checking: An overview
 RV 2010
, 2010
"... Quantitative properties of stochastic systems are usually specified in logics that allow one to compare the measure of executions satisfying certain temporal properties with thresholds. The model checking problem for stochastic systems with respect to such logics is typically solved by a numerical a ..."
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Cited by 28 (6 self)
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Quantitative properties of stochastic systems are usually specified in logics that allow one to compare the measure of executions satisfying certain temporal properties with thresholds. The model checking problem for stochastic systems with respect to such logics is typically solved by a numerical
On statistical model checking of stochastic systems
 In Etessami, K., Rajamani, S.K., eds.: CAV. Volume 3576 of Lecture Notes in Computer Science
, 2005
"... Abstract. Statistical methods to model check stochastic systems have been, thus far, developed only for a sublogic of continuous stochastic logic (CSL) that does not have steady state operator and unbounded until formulas. In this paper, we present a statistical model checking algorithm that also ve ..."
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Cited by 48 (2 self)
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Abstract. Statistical methods to model check stochastic systems have been, thus far, developed only for a sublogic of continuous stochastic logic (CSL) that does not have steady state operator and unbounded until formulas. In this paper, we present a statistical model checking algorithm that also
Distributed Parametric and Statistical Model Checking ∗
"... Statistical Model Checking (SMC) is a tradeoff between testing and formal verification. The core idea of the approach is to conduct some simulations of the system and verify if they satisfy some given property. In this paper we show that SMC is easily parallelizable on a master/slaves architecture ..."
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Cited by 2 (0 self)
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Statistical Model Checking (SMC) is a tradeoff between testing and formal verification. The core idea of the approach is to conduct some simulations of the system and verify if they satisfy some given property. In this paper we show that SMC is easily parallelizable on a master/slaves architecture
Statistical Model Checking for Biological Applications
"... In this paper we survey recent work on the use of statistical model checking techniques for biological applications. We begin with an overview of the basic modelling techniques for biochemical reactions and their corresponding stochastic simulation algorithm the Gillespie algorithm. We continue by ..."
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In this paper we survey recent work on the use of statistical model checking techniques for biological applications. We begin with an overview of the basic modelling techniques for biochemical reactions and their corresponding stochastic simulation algorithm the Gillespie algorithm. We continue
On Hypothesis testing for Statistical Model Checking
, 2014
"... Hypothesis testing is an important part of Statistical Model Checking (SMC). It is typically used to verify statements of the form p> p0 or p < p0, where p is an unknown probability intrinsic to the system model and p0 is a given threshold value. Many techniques for this have been introduced ..."
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Hypothesis testing is an important part of Statistical Model Checking (SMC). It is typically used to verify statements of the form p> p0 or p < p0, where p is an unknown probability intrinsic to the system model and p0 is a given threshold value. Many techniques for this have been introduced
RewriteBased Statistical Model Checking of WMTL
"... Abstract. We present a new technique for verifying Weighted Metric Temporal Logic (WMTL) properties of Weighted Timed Automata. Our approach relies on Statistical Model Checking combined with a new monitoring algorithm based on rewriting rules. Contrary to existing monitoring approaches for WMTL o ..."
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Cited by 3 (3 self)
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Abstract. We present a new technique for verifying Weighted Metric Temporal Logic (WMTL) properties of Weighted Timed Automata. Our approach relies on Statistical Model Checking combined with a new monitoring algorithm based on rewriting rules. Contrary to existing monitoring approaches for WMTL
Time for statistical model checking of realtime systems
 In CAV
, 2011
"... Abstract. We propose the first tool for solving complex (some undecidable) problems of timed systems by using Statistical Model Checking (SMC). The tool monitors several runs of the system, and then relies on statistical algorithms to get an estimate of the correctness of the entire design. Contrar ..."
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Cited by 16 (4 self)
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Abstract. We propose the first tool for solving complex (some undecidable) problems of timed systems by using Statistical Model Checking (SMC). The tool monitors several runs of the system, and then relies on statistical algorithms to get an estimate of the correctness of the entire design
Statistical Model Checking for Markov Decision Processes
"... Abstract—Statistical Model Checking (SMC) is a computationally very efficient verification technique based on selective system sampling. One well identified shortcoming of SMC is that, unlike probabilistic model checking, it cannot be applied to systems featuring nondeterminism, such as Markov Decis ..."
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Cited by 18 (1 self)
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Abstract—Statistical Model Checking (SMC) is a computationally very efficient verification technique based on selective system sampling. One well identified shortcoming of SMC is that, unlike probabilistic model checking, it cannot be applied to systems featuring nondeterminism, such as Markov
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