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A Compositional Framework for Quantitative Online Monitoring over Continuous-Time Signals

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Runtime Verification (RV 2021)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12974))

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Abstract

We investigate online monitoring algorithms over dense-time and continuous-time signals for properties written in metric temporal logic (MTL). We consider an abstract algebraic semantics based on complete lattices, which subsumes the Boolean (qualitative) semantics and the real-valued robustness (quantitative) semantics. Our semantics also extends to truth values that are partially ordered and allows the modeling of uncertainty in satisfaction. We propose a compositional approach for the construction of online monitors based on a class of infinite-state deterministic signal transducers that (1) are allowed to produce the output signal with some bounded delay relative to the input signal, and (2) do not introduce unbounded variability in the output signal. A key ingredient of our monitoring framework is a novel efficient algorithm for sliding-window aggregation over dense-time signals.

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Acknowledgments

This research was supported in part by US National Science Foundation award 2008096.

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Authors and Affiliations

  1. Rice University, Houston, TX, 77005, USA

    Konstantinos Mamouras, Agnishom Chattopadhyay & Zhifu Wang

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  1. Konstantinos Mamouras
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  2. Agnishom Chattopadhyay
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  3. Zhifu Wang
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Correspondence to Konstantinos Mamouras .

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  1. University of Virginia, Charlottesville, VA, USA

    Lu Feng

  2. Ben-Gurion University of the Negev, Be'er Sheva, Israel

    Dana Fisman

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Mamouras, K., Chattopadhyay, A., Wang, Z. (2021). A Compositional Framework for Quantitative Online Monitoring over Continuous-Time Signals. In: Feng, L., Fisman, D. (eds) Runtime Verification. RV 2021. Lecture Notes in Computer Science(), vol 12974. Springer, Cham. https://doi.org/10.1007/978-3-030-88494-9_8

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