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Symbolic Runtime Verification for Monitoring Under Uncertainties and Assumptions

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Automated Technology for Verification and Analysis (ATVA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13505))

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Abstract

Runtime Verification deals with the question of whether a run of a system adheres to its specification. This paper studies runtime verification in the presence of partial knowledge about the observed run, particularly where input values may not be precise or may not be observed at all. We also allow declaring assumptions on the execution which permits to obtain more precise verdicts also under imprecise inputs. We encode the specification into a symbolic formula that the monitor solves iteratively, when more observations are given. We base our framework on stream runtime verification, which allows to express temporal correctness properties not only in the Boolean but also in richer logical theories. While in general our approach requires to consider larger and larger sets of formulas, we identify domains (including Booleans and Linear Algebra) for which pruning strategies exist, which allow to monitor with constant memory (i.e. independent of the length of the observation) while preserving the same inference power as the monitor that remembers all observations. We empirically exhibit the power of our technique using a prototype implementation under two important cases studies: software for testing car emissions and heart-rate monitoring.

This work was funded in part by the Madrid Regional Government under project “S2018/TCS-4339 (BLOQUES-CM)” and by a research grant from Nomadic Labs and the Tezos Foundation.

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Notes

  1. 1.

    Note that for our symbolic approach assumptions can indeed be considered as a stream specification of type Boolean which has to be true at every time instant.

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Author information

Authors and Affiliations

  1. University of Lübeck, Lübeck, Germany

    Hannes Kallwies & Martin Leucker

  2. IMDEA Software Institute, Madrid, Spain

    César Sánchez

Authors
  1. Hannes Kallwies
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  2. Martin Leucker
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  3. César Sánchez
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Correspondence to Hannes Kallwies .

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Editors and Affiliations

  1. Université Paris Diderot, Paris, France

    Ahmed Bouajjani

  2. Brno University of Technology, Brno, Czech Republic

    Lukáš Holík

  3. Chinese Academy of Sciences, Beijing, China

    Zhilin Wu

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Kallwies, H., Leucker, M., Sánchez, C. (2022). Symbolic Runtime Verification for Monitoring Under Uncertainties and Assumptions. In: Bouajjani, A., Holík, L., Wu, Z. (eds) Automated Technology for Verification and Analysis. ATVA 2022. Lecture Notes in Computer Science, vol 13505. Springer, Cham. https://doi.org/10.1007/978-3-031-19992-9_8

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  • DOI: https://doi.org/10.1007/978-3-031-19992-9_8

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