Yadav, D. (2024). From Fault Injection to Formal Verification: A Holistic Approach to Fault Diagnosis in Cyber-Physical Systems. In ISSTA 2024: Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (pp. 1896–1900). Association for Computing Machinery. https://doi.org/10.1145/3650212.3685552
Cyber-Physical Systems (CPSs) face growing complexity, especially in safety-critical areas. Ensuring their correctness is vital to maintain full operational capacity, as undetected failures can be both costly and life-threatening. Therefore, advanced fault diagnosis procedures are essential for thorough CPS testing, enabling accurate fault detection, explanation, and rectification. This doctoral research contributes to the field by developing novel tools and techniques to enhance fault-based testing and diagnosis of CPSs.
Our research focuses on testing of CPS data ow models created in Simulink, validated against strict formal specifications. Our contributions include (i) an automated tool for systematic fault injection, (ii) a bio-inspired global optimization algorithm, (iii) a robust fault localization method, (iv) a novel approach to mutation testing for evaluating test suites against formal properties, and (v) a new coverage criterion tailored for CPS data ow models. This comprehensive approach off ers significant improvements over existing methods, ensuring thorough testing across various scenarios. We validate the e ffectiveness of our solutions using publicly available benchmarks from various domains. Our findings open new perspectives on CPS testing, laying the foundation for more robust CPSs.
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Additional information:
Drishti Yadav. 2024. From Fault Injection to Formal Verification: A Holistic Approach to Fault Diagnosis in Cyber-Physical Systems. In Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA ’24), September 16–20, 2024, Vienna, Austria. ACM, New York, NY, USA, 5 pages. https://doi.org/10.1145/3650212.3685552
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Research Areas:
Computer Engineering and Software-Intensive Systems: 70% Modeling and Simulation: 30%