The Probabilistic Model Checker Storm
About
We present the probabilistic model checker Storm. Storm supports the analysis of discrete- and continuous-time variants of both Markov chains and Markov decision processes. Storm has three major distinguishing features. It supports multiple input languages for Markov models, including the JANI and PRISM modeling languages, dynamic fault trees, generalized stochastic Petri nets, and the probabilistic guarded command language. It has a modular set-up in which solvers and symbolic engines can easily be exchanged. Its Python API allows for rapid prototyping by encapsulating Storm's fast and scalable algorithms. This paper reports on the main features of Storm and explains how to effectively use them. A description is provided of the main distinguishing functionalities of Storm. Finally, an empirical evaluation of different configurations of Storm on the QComp 2019 benchmark set is presented.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Policy Synthesis | Grid World | -- | 16 | |
| POMDP Policy Synthesis | Hallway | Execution Time0.01 | 4 | |
| POMDP Policy Synthesis | cards-removed 2 | Time0.01 | 4 | |
| POMDP Policy Synthesis | cards-removed 3 | Execution Time1 | 4 | |
| POMDP Policy Synthesis | cards removed-4 | Time2 | 4 | |
| POMDP Policy Synthesis | cards-added 2 | Execution Time0.01 | 4 | |
| POMDP Policy Synthesis | cards-added-3 | Execution Time1 | 4 | |
| POMDP Policy Synthesis | cheese-maze-det | Execution Time0.01 | 4 | |
| POMDP Policy Synthesis | rocks (N=4) | Synthesis Time7 | 4 | |
| POMDP Policy Synthesis | cheese-maze | Execution Time231.6 | 4 |