Abstract
With the increasing complexity and scale of software-intensive systems, model-based system development requires composable system models and composition operators.
In line with such a vision, this paper describes our experience in modeling the behavior of the MVM-Adapt, an adaptive version of the Mechanical Ventilator Milano that has been designed, certified, and deployed during the COVID-19 pandemic for treating pneumonia. To keep the complexity of the requirements and models under control, we exploited a compositional modeling technique for discrete-event systems based on Abstract State Machines (ASMs). Essentially, separate ASMs represent the behavior of interacting subsystems of the MVM with their new adaptive functionalities; they can communicate with each other through I/O events, and co-operate by a precise orchestration schema.
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Notes
- 1.
MVM-Adapt (Milano Ventilatore Meccanico Adaptive in the presence of uncertainty, FISR (Covid-19) project, funded in 2021.
- 2.
All models and analysis artifacts are available in https://github.com/asmeta/asmeta_based_applications/tree/main/MVM/MVM%20Cosimulation%20ABZ2023.
- 3.
Note that these complex formulas have been modeled, but they are not shown here to keep simple the presentation of the case study.
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Bonfanti, S., Riccobene, E., Santandrea, D., Scandurra, P. (2023). Modeling the MVM-Adapt System by Compositional I/O Abstract State Machines. In: Glässer, U., Creissac Campos, J., Méry, D., Palanque, P. (eds) Rigorous State-Based Methods. ABZ 2023. Lecture Notes in Computer Science, vol 14010. Springer, Cham. https://doi.org/10.1007/978-3-031-33163-3_8
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