Abstract
Model checking has been extensively used to verify various systems. However, this usually has been done by experts who have a good understanding of model checking and who are familiar with the syntax of both modelling and property specification languages. Unfortunately, this is not an easy task for nonexperts to learn description languages for modelling and formal logics/languages for property specification. In particular, property specification is very daunting and error-prone for nonexperts. In this paper, we present a methodology to facilitate probabilistic model checking for nonexperts. The methodology helps nonexpert users model their systems and express their requirements without any knowledge of the modelling and property specification languages.
Highlights
Model checking [1] is a computational and algorithmic verification technique analysing if certain requirements hold in a system
Probabilistic model checking tools have been used to verify various systems, this usually has been done by experts who have a good understanding of model checking and who are familiar with the syntax of both modelling and property specification languages
We present a methodology to facilitate probabilistic model checking for nonexperts
Summary
Model checking [1] is a computational and algorithmic verification technique analysing if certain requirements hold in a system. These requirements are expressed as formal properties, such as temporal logic formulas. Since model checking provides a comprehensive and an exhaustive computational analysis, it can reveal all possible system behaviours, which cannot be normally done by simulation or testing techniques. For this reason, it has been applied to various engineering problems, for example, hardware verification, software and programme verification, analysis of communication protocols, and safety-critical systems
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