Probabilistic model checking

Model checking of Markov models

Probabilistic model checking allows to analyses Markov models such as discrete-time Markov chains (DTMC), Markov decision processes (MDP), continuous-time Markov chains (CTMC) and Markov automata (MA). Model checking allows to answer questions such as “what is the probability that the nuclear power plants has a critical failure within 50 years?” or “what is the optimal strategy to minimize energy consumption in a satellite while still performing the required tasks?”.


I am a main developer and maintainer of the Storm model checker (Hensel et al., 2022). Storm is state-of-the-art for probabilistic model checking as witnessed in the Quantitative Verification Competition (QComp). Storm supports many input formats, algorithms, and queries from the literature, and is used by a growing number of other researcher and tools.



  1. STTT
    Christian Hensel, Sebastian JungesJoost-Pieter KatoenTim Quatmann, and Matthias Volk
    Int. J. Softw. Tools Technol. Transf., 2022