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Data · dataset · 2026

Risk-Aware Runtime Monitoring and Mitigation: Semantics, Abstraction, and Monitor Memory (AE)

Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.6084/m9.figshare.34033377.v1

<p dir="ltr">This artifact accompanies the paper “Risk-Aware Runtime Monitoring and Mitigation: Semantics, Abstraction, and Monitor Memory”.

Description

It includes an executable infusion-pump model supporting exact finite-horizon predictive risk analysis and a FastAPI-based prototype demonstrating history-dependent hazard monitoring, consequence-based risk computation, and policy-triggered mitigation. Experiments demonstrate different risks for histories reaching the same declared system state, validate incremental monitoring against full-prefix references, compare exact predictive monitor quotients, and measure runtime and memory costs.

Conservative bucket-monitoring experiments quantify extra hazard and mitigation verdicts, including their episode counts and durations, and check that exact violations are not missed. The package includes prebuilt Docker images for ARM64 and x86-64, source code, automated tests, reproduction scripts, reference results, and documentation for evaluation and reuse. With Docker and the documented prerequisites installed, the default evaluation runs offline after download.</p>

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Image 65%
Provenance · 3 source records, 24 field assertions
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ZivaHuboai:figshare.com:article/340333778 d agoJSON v1
Deakin Research Onlineoai:figshare.com:article/340333778 d agoJSON v1
DMU Figshareoai:figshare.com:article/340333778 d agoJSON v1
FieldAssertionExtractorEvidence
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