The overall goal of the ModelFusion project is to develop model-based solutions that lead to substantial reductions in the costs associated with the development, and verification and validation of cyber-physical systems, which are large-scale, heterogeneous, embedded software systems used in many industry sectors, including Maritime and Energy. Since the beginning of the ModelFusion project in 2011, we have been active in two areas of research to achieve the project objectives. Specifically, we devised, developed and implemented solutions for model-based analysis and testing of safety-related performance properties, and scalable techniques to facilitate consistent configuration of Cyber-Physical Systems.
In the context of the first research direction, we focused on performance analysis and testing of Real-time Embedded System. In particular, we have developed innovative solutions for worst-case scenario analysis, which both derive design guidelines to maximize the system performance, and generate test cases that reveal potential performance flaws in the real-time software. The solutions we provide are strongly geared towards industrial adoption due to two main factors. First, our approaches are platform-independent and fully integrated with model-based development frameworks, as they model the target system specification in the standard UML/MARTE profile. Second, these approaches provide flexibility in achieving the desired value-cost tradeoff of the analysis through the use of several optimization techniques, such as Constraint Programming, Metaheuristics, and hybrid search strategies.
For the second line of our research, the effort has been focused on improving a model-based semi-automated configuration framework named Magic. Distinguished features of the Magic framework are (1) instant validation of user decisions, to ensure the overall consistency of the configuration data, and (2) providing configuration guidance based on user decisions. Our goal in the context of the ModelFusion project is to improve the usability of the Magic framework. In particular, we have proposed new techniques for providing better configuration guidance, while reducing the response time. To achieve this, we rely on constraint programming techniques, in particular constraint propagation over finite domains. Furthermore, we are designing advanced configuration functionalities that can provide more flexibility, and better user experience.
The Research Council of Norway, FRITEK program