IoT systems' complexity and susceptibility to failures pose significant challenges in ensuring their reliable operation. Failures can be internally generated or caused by external factors, impacting both the system's correctness and its surrounding environment. To investigate these complexities, various modeling approaches have been proposed to raise the level of abstraction, facilitating automation and analysis. Failure-Logic Analysis (FLA) is a technique that helps predict potential failure scenarios by defining how a component's failure logic behaves and spreads throughout the system. However, manually specifying FLA rules can be arduous and error-prone, leading to incomplete or inaccurate specifications. In this paper, we propose adopting testing methodologies to improve the completeness and correctness of these rules. How failures may propagate within an IoT system can be observed by systematically injecting failures, while running test cases to collect evidence useful to add, complete and refine FLA rules.
Clerissi, D., Rocco, J., Di Ruscio, D., Di Sipio, C., Ihirwe, F., Mariani, L., et al. (2023). Supporting Early-Safety Analysis of IoT Systems by Exploiting Testing Techniques. In Proceedings - 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2023 (pp.520-529). Institute of Electrical and Electronics Engineers Inc. [10.1109/MODELS-C59198.2023.00089].
Supporting Early-Safety Analysis of IoT Systems by Exploiting Testing Techniques
Clerissi, D;Mariani, L;Micucci, D;Rossi, MT;
2023
Abstract
IoT systems' complexity and susceptibility to failures pose significant challenges in ensuring their reliable operation. Failures can be internally generated or caused by external factors, impacting both the system's correctness and its surrounding environment. To investigate these complexities, various modeling approaches have been proposed to raise the level of abstraction, facilitating automation and analysis. Failure-Logic Analysis (FLA) is a technique that helps predict potential failure scenarios by defining how a component's failure logic behaves and spreads throughout the system. However, manually specifying FLA rules can be arduous and error-prone, leading to incomplete or inaccurate specifications. In this paper, we propose adopting testing methodologies to improve the completeness and correctness of these rules. How failures may propagate within an IoT system can be observed by systematically injecting failures, while running test cases to collect evidence useful to add, complete and refine FLA rules.
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