Probabilistic model checking is a variant of traditional model checking where models and properti... more Probabilistic model checking is a variant of traditional model checking where models and properties can be associated with probabilistic features. This allows for more complicated forms of system analysis beyond just checking correctness, including for instance measuring reliability and performance. Probabilistic model checking can also be used to analyse systems that are inherently random, which are problematic for traditional model checkers. This report covers the basics of the theoretical model and property constructions commonly used in probabilistic model checking, and provides an overview on the practise by presenting the features and usage of one such model checker, namely the PRISM tool, in detail through practical examples. Several other probabilistic model checkers are also presented, albeit in less detail, to provide an overview on the current state-of-the-art in the field. As most instrumentation and control systems are designed to provide high reliability in inherently random environments, probabilistic model checking is a very suitable tool for analysing such systems.
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