Publikation: Causal Reasoning for Safety in Hennessy Milner Logic
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2020
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Fundamenta Informaticae. IOS Press. 2020, 173(2-3), pp. 217-251. ISSN 0169-2968. eISSN 1875-8681. Available under: doi: 10.3233/FI-2020-1922
Zusammenfassung
Determining and computing root causes in system failures is a significant issue in science and engineering. In this paper, we introduce a notion of causality for explaining counterexamples in system analysis based on formal models. The counter-examples are produced by checking for hazardous situations expressed in the Hennessy-Milner Logic, in the context of Labelled Transition System models. We also introduce CauseJMu, a tool for automatically identifying such causal computations within a system model. CauseJMu relies on encoding causality in terms of an extension of Hennessy-Milner Logic to recursive formulae with data. The encodings enable deciding whether a certain computation is causal or not, using the mCRL2 model checker.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Cauality, Counterfactual causal reasoning, Concurrency, Labelled Transition Systems, Hennessy Milner Logic, Safety, Model-checking, Process algebra, mCRL2
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CALTAIS, Georgiana, Mohammad Reza MOUSAVI, Hargurbir SINGH, 2020. Causal Reasoning for Safety in Hennessy Milner Logic. In: Fundamenta Informaticae. IOS Press. 2020, 173(2-3), pp. 217-251. ISSN 0169-2968. eISSN 1875-8681. Available under: doi: 10.3233/FI-2020-1922BibTex
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title={Causal Reasoning for Safety in Hennessy Milner Logic},
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volume={173},
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journal={Fundamenta Informaticae},
pages={217--251},
author={Caltais, Georgiana and Mousavi, Mohammad Reza and Singh, Hargurbir}
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<dcterms:abstract xml:lang="eng">Determining and computing root causes in system failures is a significant issue in science and engineering. In this paper, we introduce a notion of causality for explaining counterexamples in system analysis based on formal models. The counter-examples are produced by checking for hazardous situations expressed in the Hennessy-Milner Logic, in the context of Labelled Transition System models. We also introduce CauseJMu, a tool for automatically identifying such causal computations within a system model. CauseJMu relies on encoding causality in terms of an extension of Hennessy-Milner Logic to recursive formulae with data. The encodings enable deciding whether a certain computation is causal or not, using the mCRL2 model checker.</dcterms:abstract>
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