Search-based Trace Diagnostic

• URL: http://arxiv.org/abs/2406.17268v1
• Date: Tue, 25 Jun 2024 04:24:21 GMT
• Title: Search-based Trace Diagnostic
• Authors: Gabriel Araujo, Ricardo Caldas, Federico Formica, Genaína Rodrigues, Patrizio Pelliccione, Claudio Menghi,
• Abstract summary: When an execution trace violates a requirement, engineers need to understand the cause of the breach. This paper proposes search-based trace-diagnostic (SBTD), a novel trace-diagnostic technique for CPS requirements.
• Score: 7.771496745635823
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Cyber-physical systems (CPS) development requires verifying whether system behaviors violate their requirements. This analysis often considers system behaviors expressed by execution traces and requirements expressed by signal-based temporal properties. When an execution trace violates a requirement, engineers need to solve the trace diagnostic problem: They need to understand the cause of the breach. Automated trace diagnostic techniques aim to support engineers in the trace diagnostic activity. This paper proposes search-based trace-diagnostic (SBTD), a novel trace-diagnostic technique for CPS requirements. Unlike existing techniques, SBTD relies on evolutionary search. SBTD starts from a set of candidate diagnoses, applies an evolutionary algorithm iteratively to generate new candidate diagnoses (via mutation, recombination, and selection), and uses a fitness function to determine the qualities of these solutions. Then, a diagnostic generator step is performed to explain the cause of the trace violation. We implemented Diagnosis, an SBTD tool for signal-based temporal logic requirements expressed using the Hybrid Logic of Signals (HLS). We evaluated Diagnosis by performing 34 experiments for 17 trace-requirements combinations leading to a property violation and by assessing the effectiveness of SBTD in producing informative diagnoses and its efficiency in generating them on a time basis. Our results confirm that Diagnosis can produce informative diagnoses in practical time for most of our experiments (33 out of 34).

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