International audienceStatistical Model Checking (SMC) is a compromise between verification and testing where executions of the systems are monitored until an algorithm from statistics can produce an estimate for the system to satisfy a given property. The objective of this introduction is to summarizes SMC as well as a series of challenges for which contributors at Isola propose a solution. Contributions include new SMC toolsets, new flexible SMC algorithms for larger classes of systems, and new applications
International audienceTransaction-level modeling with SystemC has been very successful in describing...
Abstract. Quantitative properties of stochastic systems are usually spec-ified in logics that allow ...
Statistical model checking is a powerful and flexible approach for formal verification of computatio...
International audienceStatistical Model Checking (SMC) is a compromise between verification and test...
We highlight the contributions made in the field of Statistical Model Checking (SMC) since its incep...
International audienceThis paper contains material for our tutorial presented at STRESS 2016. This i...
Statistical model checking (SMC) has been used to verify both biological and P systems, but differe...
Statistical Model Checking (SMC) is a trade-off between testing and formal verification. The core id...
We propose the first tool for solving complex (some undecidable) problems of timed systems by using ...
Statistical Model Checking (SMC) is a powerful and widely used approach that consists in estimating ...
Abstract. We propose the first tool for solving complex (some unde-cidable) problems of timed system...
Statistical Model Checking (SMC) is a powerful and widely used approach that consists in extracting ...
Statistical model checking (SMC) is an analysis method that circumvents the state space explosion pr...
International audienceQuantitative properties of stochastic systems are usually specified in logics ...
Statistical model-checking is a recent technique used for both verification and performance analysis...
International audienceTransaction-level modeling with SystemC has been very successful in describing...
Abstract. Quantitative properties of stochastic systems are usually spec-ified in logics that allow ...
Statistical model checking is a powerful and flexible approach for formal verification of computatio...
International audienceStatistical Model Checking (SMC) is a compromise between verification and test...
We highlight the contributions made in the field of Statistical Model Checking (SMC) since its incep...
International audienceThis paper contains material for our tutorial presented at STRESS 2016. This i...
Statistical model checking (SMC) has been used to verify both biological and P systems, but differe...
Statistical Model Checking (SMC) is a trade-off between testing and formal verification. The core id...
We propose the first tool for solving complex (some undecidable) problems of timed systems by using ...
Statistical Model Checking (SMC) is a powerful and widely used approach that consists in estimating ...
Abstract. We propose the first tool for solving complex (some unde-cidable) problems of timed system...
Statistical Model Checking (SMC) is a powerful and widely used approach that consists in extracting ...
Statistical model checking (SMC) is an analysis method that circumvents the state space explosion pr...
International audienceQuantitative properties of stochastic systems are usually specified in logics ...
Statistical model-checking is a recent technique used for both verification and performance analysis...
International audienceTransaction-level modeling with SystemC has been very successful in describing...
Abstract. Quantitative properties of stochastic systems are usually spec-ified in logics that allow ...
Statistical model checking is a powerful and flexible approach for formal verification of computatio...