Bayesian statistical model checking with application to Stateflow/Simulink verification
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We address the problem of model checking stochastic systems, i.e., checking whether a stochastic system satisfies a certain temporal property with a probability greater (or smaller) than a fixed threshold. In particular, we present a Statistical Model Checking (SMC) approach base
We introduce the concept of generalized probabilistic queries in Dynamic Bayesian Networks (DBN) — computing P (φ1|φ2), where φi is a formula in temporal logic encoding an equivalence class of trajectories through the variables of the model. Generalized queries include as special
Transaction-level modeling with SystemC has been very successful in describing the behavior of embedded systems by providing high-level executable models, in which many of them have an inherent probabilistic behavior, i.e., random data, unreliable components. It is crucial to eva
The evolution of automotive systems has been rapid. Nowadays, electronic brains control dozens of functions in vehicles, like braking, cruising, etc. Model-based design approaches, in environments such as MATLAB Simulink, seem to help in addressing the ever-increasing need to enh
Transaction-level modeling with SystemC has been very successful in describing the behavior of embedded systems by providing high-level executable models, in which many of them have inherent probabilistic behaviors, e.g., random data and unreliable components. It thus is crucial