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Földvári A, Pataricza A. 2025. Model-driven, logic-supported exploratory dependability analysis. VERDI 2025.

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Conference:
3rd International Workshop on Verification & Validation of Dependable Cyber-Physical Systems (VERDI 2025), co-located with the 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2025), 23. June 2025, Naples, Italy

Authors:
Földvári A, Pataricza A.

Abstract:
Analyzing empirical dependability data now exceeds domain experts’ capabilities without adequate machine support. This is due to the complexity of modern IT systems, their many interdependent features, and the extensive time series involved. This paper presents a model-driven approach to Exploratory Data Analysis (EDA), which is guided by formal logic reasoning over an abstract data model. This supports domain experts in formulating and validating hypotheses, as well as guiding the exploration process.
Observations are transformed into qualitative abstractions, facilitating Answer Set Programming (ASP) based formal reasoning over system behavior and dependencies. Counterexample-guided inductive learning (CEGIL) and Rough Set Theory (RST) are used for iterative hypothesis refinement and  uncertainty management.
The integrated framework enables precise, transparent, and systematic dependability assessment  using common-sense engineering principles, thereby assisting analysts in the evaluation process with pertinent expert insights.

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