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Formal specification and validation of the MVM-Adapt system using Compositional I/O Abstract State Machines

Academic Article
Publication Date:
2025
Citation:
Formal specification and validation of the MVM-Adapt system using Compositional I/O Abstract State Machines / S. Bonfanti, E. Riccobene, P. Scandurra. - In: SCIENCE OF COMPUTER PROGRAMMING. - ISSN 0167-6423. - 244:(2025), pp. 103299.1-103299.21. [10.1016/j.scico.2025.103299]
abstract:
To face complexity and scalability, the design of software-intensive systems requires the decomposition of the system into components, each modeled and analyzed separately from the others, and the composition of their analysis. Moreover, compositional model simulation is recognized as the only alternative available in practice when systems are large and complex, like in the cyber-physical domain, and intrinsically require combining the specification of ensembles of different parts (subsystems). Therefore, the need for simulation engines for composed model execution is getting a growing interest. Along this research line, this paper presents the results of the compositional modeling and validation by scenarios of an industrial medical system, called MVM-Adapt, that we designed as an adaptive version of an existing mechanical lung ventilator deployed and certified to treat pneumonia during the COVID-19 pandemic. We exploit the I/O Abstract State Machine formalism to model the device components as separate and interacting sub-systems that communicate through I/O events and adapt the device ventilation mode at run-time based on the health parameters of the patient. An orchestrated simulation coordinates the overall execution of these communicating I/O ASMs by exploiting suitable workflow patterns. This compositional simulation technique has proved to be useful in practice to validate the new adaptive MVM's behavior and thus to support architects in better understanding this new mode of operation of the prototyped system.
IRIS type:
01 - Articolo su periodico
Keywords:
Abstract State Machines; Compositional model-based simulation; Discrete Event Systems modeling; Models@run.time;
List of contributors:
S. Bonfanti, E. Riccobene, P. Scandurra
Authors of the University:
RICCOBENE ELVINIA MARIA ( author )
Link to information sheet:
https://air.unimi.it/handle/2434/1234300
Full Text:
https://air.unimi.it/retrieve/handle/2434/1234300/3301955/1-s2.0-S0167642325000383-main.pdf
Project:
SAFEST: Trust assurance of Digital Twins for medical cyber-physical systems
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