Search-based Trace Diagnostic
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866911931018772480 |
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| author | Araujo, Gabriel Caldas, Ricardo Formica, Federico Rodrigues, Genaína Pelliccione, Patrizio Menghi, Claudio |
| author_facet | Araujo, Gabriel Caldas, Ricardo Formica, Federico Rodrigues, Genaína Pelliccione, Patrizio Menghi, Claudio |
| contents | 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). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_17268 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Search-based Trace Diagnostic Araujo, Gabriel Caldas, Ricardo Formica, Federico Rodrigues, Genaína Pelliccione, Patrizio Menghi, Claudio Software Engineering 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). |
| title | Search-based Trace Diagnostic |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2406.17268 |