2026-10-09T20:38:55Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34033377 2026-09-30T15:20:36Z category_28918 category_29188 category_29185 item_type_9 month_year_09_2026

Risk-Aware Runtime Monitoring and Mitigation: Semantics, Abstraction, and Monitor Memory (AE) Sepehr Amir (25144590) Software and application security Programming languages Formal methods for software Quantitative verification Risk-aware computation Runtime monitoring <p dir="ltr">This artifact accompanies the paper “Risk-Aware Runtime Monitoring and Mitigation: Semantics, Abstraction, and Monitor Memory”. 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> 2026-09-30T15:20:36Z Software Software 10.6084/m9.figshare.34033377.v1 https://figshare.com/articles/software/Risk-Aware_Runtime_Monitoring_and_Mitigation_Semantics_Abstraction_and_Monitor_Memory_AE_/34033377 MIT