Assessing the functional feasibility of variability-intensive data flow-oriented systems

Data-flow oriented embedded systems, such as automotive systems used to render HMI (e.g., instrument clusters, infotainments), are increasingly built from highly variable specifications while targeting different constrained hardware platforms configurable in a finegrained way. These variabilities at two different levels lead to a huge number of possible embedded system solutions, which feasibility is extremely complex and tedious to predetermine. In this paper, we propose a tooled approach that capture high level specifications as variable dataflows, and targeted platforms as variable component models. Dataflows can then be mapped onto platforms to express a specification of such variability-intensive systems. The proposed tool support transforms this specification into structural and behavioral variability models and reuses automated reasoning techniques to explore and assess the feasibility of all variants in a single run. We also report on the application of the proposed approach to an industrial case study of automotive instrument cluster.