We present an extensive collection of quantitative models to facilitate the development, comparison, and benchmarking of new verification algorithms and tools. All models have a formal semantics in terms of extensions of Markov chains, are provided in the Jani format, and are documented by a comprehensive set of metadata. The collection is highly diverse: it includes established probabilistic verification and planning benchmarks, industrial case studies, models of biological systems, dynamic fault trees, and Petri net examples, all originally specified in a variety of modelling languages. It archives detailed tool performance data for each model, enabling immediate comparisons between tools and among tool versions over time. The collection is easy to access via a client-side web application at qcomp.org with powerful search and visualisation features. It can be extended via a Git-based submission process, and is openly accessible according to the terms of the CC-BY license.
CITATION STYLE
Hartmanns, A., Klauck, M., Parker, D., Quatmann, T., & Ruijters, E. (2019). The quantitative verification benchmark set. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11427 LNCS, pp. 344–350). Springer Verlag. https://doi.org/10.1007/978-3-030-17462-0_20
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