Abstract
Statistical Model Checking (SMC) [19,16,21,23,15] is an approach that has recently been proposed as new validation technique for large-scale, complex systems. The core idea of SMC is to conduct some simulations of the system, monitor them, and then use statistical methods (including sequential hypothesis testing or Monte Carlo simulation) in order to decide with some degree of confidence whether the system satisfies the property or not. By nature, SMC is a compromise between testing and classical formal method techniques. Simulation-based methods are known to be far less memory and time intensive than exhaustive ones, and are some times the only option.
Work partially supported by the VKR Centre of Excellence MT-LAB, the Sino-Danish Basic Research Center IDEA4CPS.
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Larsen, K.G. (2012). Statistical Model Checking, Refinement Checking, Optimization, … for Stochastic Hybrid Systems. In: Jurdziński, M., Ničković, D. (eds) Formal Modeling and Analysis of Timed Systems. FORMATS 2012. Lecture Notes in Computer Science, vol 7595. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33365-1_2
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