Runtime Verification via Rational Monitor with Imperfect Information

Trusting software systems, particularly autonomous ones, is challenging. To address this, formal verification techniques can ensure these systems behave as expected. Runtime Verification (RV) is a leading, lightweight method for verifying system behaviour during execution. However, traditional RV assumes perfect information, meaning the monitoring component perceives everything accurately. This assumption often fails, especially with autonomous systems operating in real-world environments where sensors might be faulty. Additionally, traditional RV considers the monitor to be passive, lacking the capability to interpret the system’s information and thus unable to address incomplete data. In this work, we extend standard RV of Linear Temporal Logic properties to accommodate scenarios where the monitor has imperfect information and behaves rationally. We outline the necessary engineering steps to update the verification pipeline and demonstrate our implementation in a case study involving robotic systems.

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Publication Details

Journal
ACM Transactions on Software Engineering and Methodology
Published
2025-05-10
DOI
https://doi.org/10.1145/3735130
Citations
1
Primary Topic
Formal Methods in Verification
Type
article
Field-Weighted Citation Impact
1.50
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article

Runtime Verification via Rational Monitor with Imperfect Information

Vadim Malvone, Angelo Ferrando
1 citations
ACM Transactions on Software Engineering and Methodology
Formal Methods in Verification
1.50
article

Runtime Verification via Rational Monitor with Imperfect Information

Vadim Malvone, Angelo Ferrando
article en
1 citations

Abstract

Trusting software systems, particularly autonomous ones, is challenging. To address this, formal verification techniques can ensure these systems behave as expected. Runtime Verification (RV) is a leading, lightweight method for verifying system behaviour during execution. However, traditional RV assumes perfect information, meaning the monitoring component perceives everything accurately. This assumption often fails, especially with autonomous systems operating in real-world environments where sensors might be faulty. Additionally, traditional RV considers the monitor to be passive, lacking the capability to interpret the system’s information and thus unable to address incomplete data. In this work, we extend standard RV of Linear Temporal Logic properties to accommodate scenarios where the monitor has imperfect information and behaves rationally. We outline the necessary engineering steps to update the verification pipeline and demonstrate our implementation in a case study involving robotic systems.

ACM Transactions on Software Engineering and MethodologyVol. 35(3)
University of Modena and Reggio Emilia (IT), Télécom Paris (FR), Institut Polytechnique de Paris (FR)
Openalex Percentile: Top 17%
Formal Methods in Verification
1.50
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