PROPhESY: A PRObabilistic ParamEter SYnthesis Tool

@inproceedings{Dehnert2015PROPhESYAP,
  title={PROPhESY: A PRObabilistic ParamEter SYnthesis Tool},
  author={Christian Dehnert and Sebastian Junges and Nils Jansen and Florian Corzilius and Matthias Volk and Harold Bruintjes and Joost-Pieter Katoen and Erika {\'A}brah{\'a}m},
  booktitle={CAV},
  year={2015}
}
We present PROPhESY, a tool for analyzing parametric Markov chains (MCs). It can compute a rational function (i.e., a fraction of two polynomials in the model parameters) for reachability and expected reward objectives. Our tool outperforms state-of-the-art tools and supports the novel feature of conditional probabilities. PROPhESY supports incremental automatic parameter synthesis (using SMT techniques) to determine “safe” and “unsafe” regions of the parameter space. All values in these… CONTINUE READING
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