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Book Sections Year : 2020

A Model-Based Combination Language for Scheduling Verification

Abstract

Cyber-Physical Systems (CPSs) are built upon discrete software and hardware components, as well as continuous physical components. Such heterogeneous systems involve numerous domains with competencies and expertise that go far beyond traditional software engineering: systems engineering. In this paper , we explore a model-based approach for systems engineering that advocates the composition of several heterogeneous artifacts (called views) into a sound and consistent system model. A model combination Language is proposed for this purpose. Thus, rather than trying to build the universal language able to capture all possible aspects of systems, the proposed language proposes to relate small subsets of languages in order to offer specific analysis capabilities while keeping a global consistency between all joined models. We demonstrate the interest of our approach through an industrial process based on Capella, which provides (among others) a large support for functional analysis from requirements to components deployment. Even though Capella is already quite expressive, it lacks support for schedulability analysis. AADL is also a language dedicated to system analysis. If it is backed with advanced schedulability tools, it lacks support for functional analysis. Thus, instead of proposing ways to add missing aspects in either Capella or AADL, we rather extract a relevant subset of both languages to build a view adequate for conducting schedulability analysis of Capella functional models. Finally, our combination language is generic enough to extract pertinent subsets of languages and combine them to build views for different experts. It also helps maintaining a global consistency between different modeling views.
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Dates and versions

hal-02430903 , version 1 (07-01-2020)

Identifiers

  • HAL Id : hal-02430903 , version 1

Cite

Hui Zhao, Ludovic Apvrille, Frédéric Mallet. A Model-Based Combination Language for Scheduling Verification. Model-Driven Engineering and Software Development, Springer International Publishing, 2020. ⟨hal-02430903⟩
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