Bridging the gap between single- and multi-model predictive runtime verification

Journal article


Angelo Ferrando, Rafael C. Cardoso, Marie Farrell, Matt Luckcuck, Fabio Papacchini, Michael Fisher and Viviana Mascardi 2022. Bridging the gap between single- and multi-model predictive runtime verification. Formal Methods in System Design. 59, p. 44–76. https://doi.org/10.1007/s10703-022-00395-7
AuthorsAngelo Ferrando, Rafael C. Cardoso, Marie Farrell, Matt Luckcuck, Fabio Papacchini, Michael Fisher and Viviana Mascardi
Abstract

This paper presents an extension of the Predictive Runtime Verification (PRV) paradigm to consider multiple models of the System Under Analysis (SUA). We call this extension Multi-Model PRV. Typically, PRV attempts to predict the satisfaction or violation of a property based on a trace and a (single) formal model of the SUA. However, contemporary node- or component-based systems (e.g. robotic systems) may benefit from monitoring based on a model of each component. We show how a Multi-Model PRV approach can be applied in either a centralised or a compositional way (where the property is compositional), as best suits the SUA. Crucially, our approach is formalism-agnostic. We demonstrate our approach using an illustrative example of a Mars Curiosity rover simulation and evaluate our contribution via a prototype implementation.

KeywordsPredictive Runtime Verification (PRV) paradigm; Mars Curiosity rover simulation; Multi-Model PRV
Year2022
JournalFormal Methods in System Design
Journal citation59, p. 44–76
PublisherSpringer
ISSN0925-9856
1572-8102
Digital Object Identifier (DOI)https://doi.org/10.1007/s10703-022-00395-7
Web address (URL)http://dx.doi.org/10.1007/s10703-022-00395-7
Output statusPublished
Publication dates18 Aug 2022
Publication process dates
Accepted05 Jul 2022
Deposited31 Jan 2023
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https://repository.derby.ac.uk/item/9w939/bridging-the-gap-between-single-and-multi-model-predictive-runtime-verification

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