A Modest Approach to Modelling and Checking Markov Automata (Artifact)

Datacite citation style:
Butkova, Y. (Yuliya) (2019): A Modest Approach to Modelling and Checking Markov Automata (Artifact). Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:98d571be-cdd4-4e5a-a589-7c5b1320e569
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Dataset
University of Twente logo
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Other licence for specific components (software): see file /modest/License.txt in the data.
Markov automata are a compositional modelling formalism with continuous stochastic time, discrete probabilities, and nondeterministic choices. In our QEST 2019 paper titled "A Modest Approach to Modelling and Checking Markov Automata", we present extensions to the Modest language and the 'mcsta' model checker of the Modest Toolset to describe and analyse Markov automata models. The verification of Markov automata models requires dedicated algorithms for time-bounded probabilistic reachability and long-run average rewards. In the paper, we describe several recently developed such algorithms as implemented in 'mcsta' and evaluate them on a comprehensive set of benchmarks. Our evaluation shows that 'mcsta' improves the performance and scalability of Markov automata model checking compared to earlier and alternative tools. This artifact contains (1) the version of 'mcsta' and (2) the model files used for our experiments, (3) the raw experimental results, and (4) Linux scripts to replicate the experiments.
history
  • 2019-09-05 first online, published, posted
publisher
4TU.Centre for Research Data
format
media types: application/octet-stream, application/x-archive, application/x-dosexec, application/x-sharedlib, application/zip, text/plain, text/x-python
organizations
University of Twente, Faculty of Electrical Engineering, Mathematics and Computer Science, Formal Methods and Tools (FMT) research
contributors
  • Hartmanns, A. (Arnd) orcid logo
  • Hermanns, H. (Holger) orcid logo

DATA

files