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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.

Christian Hensel, Sebastian Junges, Joost-Pieter Katoen, Tim Quatmann, Matthias Volk• 2020

Related benchmarks

TaskDatasetResultRank
Policy SynthesisGrid World--
16
POMDP Policy SynthesisHallway
Execution Time0.01
4
POMDP Policy Synthesiscards-removed 2
Time0.01
4
POMDP Policy Synthesiscards-removed 3
Execution Time1
4
POMDP Policy Synthesiscards removed-4
Time2
4
POMDP Policy Synthesiscards-added 2
Execution Time0.01
4
POMDP Policy Synthesiscards-added-3
Execution Time1
4
POMDP Policy Synthesischeese-maze-det
Execution Time0.01
4
POMDP Policy Synthesisrocks (N=4)
Synthesis Time7
4
POMDP Policy Synthesischeese-maze
Execution Time231.6
4
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