Search-based Trace Diagnostic
<|reference_start|>Search-based Trace Diagnostic: 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).<|reference_end|>
@article{araujo2024search-based,
    title={Search-based Trace Diagnostic},
    author={Gabriel Araujo, Ricardo Caldas, Federico Formica, Gena'ina Rodrigues,
  Patrizio Pelliccione, Claudio Menghi},
    journal={arXiv preprint arXiv:2406.17268},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.17268},
    primaryClass={cs.SE}
}