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Ontology-Mediated Probabilistic Model Checking

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Integrated Formal Methods (IFM 2019)

Abstract

Probabilistic model checking (PMC) is a well-established method for the quantitative analysis of dynamic systems. Description logics (DLs) provide a well-suited formalism to describe and reason about terminological knowledge, used in many areas to specify background knowledge on the domain. We investigate how such knowledge can be integrated into the PMC process, introducing ontology-mediated PMC. Specifically, we propose a formalism that links ontologies to dynamic behaviors specified by guarded commands, the de-facto standard input formalism for PMC tools such as Prism. Further, we present and implement a technique for their analysis relying on existing DL-reasoning and PMC tools. This way, we enable the application of standard PMC techniques to analyze knowledge-intensive systems. Our approach is implemented and evaluated on a multi-server system case study, where different DL-ontologies are used to provide specifications of different server platforms and situations the system is executed in.

The authors are supported by the DFG through the Collaborative Research Centers CRC 912 (HAEC) and TRR 248 (see https://perspicuous-computing.science, project ID 389792660), the Cluster of Excellence EXC 2050/1 (CeTI, project ID 390696704, as part of Germany’s Excellence Strategy), and the Research Training Groups QuantLA (GRK 1763) and RoSI (GRK 1907).

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Notes

  1. 1.

    Hardware setup: Intel Xeon E5-2680@2.70 GHz, 128 GB RAM; Turbo Boost and HT enabled; Debian GNU/Linux 9.1.

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Correspondence to Clemens Dubslaff .

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Dubslaff, C., Koopmann, P., Turhan, AY. (2019). Ontology-Mediated Probabilistic Model Checking. In: Ahrendt, W., Tapia Tarifa, S. (eds) Integrated Formal Methods. IFM 2019. Lecture Notes in Computer Science(), vol 11918. Springer, Cham. https://doi.org/10.1007/978-3-030-34968-4_11

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  • DOI: https://doi.org/10.1007/978-3-030-34968-4_11

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