Formalizing Cyber--Physical System Model Transformation via Abstract Interpretation

Model transformation tools assist system designers by reducing the labor--intensive task of creating and updating models of various aspects of systems, ensuring that modeling assumptions remain consistent across every model of a system, and identifying constraints on system design imposed by these modeling assumptions. We have proposed a model transformation approach based on abstract interpretation, a static program analysis technique. Abstract interpretation allows us to define transformations that are provably correct and specific. This work develops the foundations of this approach to model transformation. We define model transformation in terms of abstract interpretation and prove the soundness of our approach. Furthermore, we develop formalisms useful for encoding model properties. This work provides a methodology for relating models of different aspects of a system and for applying modeling techniques from one system domain, such as smart power grids, to other domains, such as water distribution networks.Comment: 8 pages, 4 figures; to appear in HASE 2019 proceeding

Journal of Telecommunications and Information Technology, nr 4

kwartalni

Simulating hybrid systems within SIMTHESys multi-formalism models

As many real world systems evolve according to phenomena characterized by a continuous time dependency, literature studied several approaches to correctly capture all their aspects. Since their analysis is not trivial, different high level approaches have been proposed, such as classical pure mathematical analysis or tool-oriented frameworks like Fluid Stochastic Petri Nets. Each approach has its specific purposes and naturally addresses some application field. This paper instead focuses on the simulation of models written in a custom Hybrid Systems (HS) formalism. The key aspect of this work is focused on the use within a framework called SIMTHESys of a function describing how the fluid variables evolve, providing more efficient simulation with respect to traditional approaches

Simulating hybrid systems within SIMTHESys multi-formalism models

As many real world systems evolve according to phenomena characterized by a continuous time dependency, literature studied several approaches to correctly capture all their aspects. Since their analysis is not trivial, different high level approaches have been proposed, such as classical pure mathematical analysis or tool-oriented frameworks like Fluid Stochastic Petri Nets. Each approach has its specific purposes and naturally addresses some application field. This paper instead focuses on the simulation of models written in a custom Hybrid Systems (HS) formalism. The key aspect of this work is focused on the use within a framework called SIMTHESys of a function describing how the fluid variables evolve, providing more efficient simulation with respect to traditional approaches