The current practice of manually configuring any non-trivial Cyber Physical Systems (CPSs) product line is often error-prone and labor-intensive. In other words, the quality and productivity of the product configuration process cannot be ensured. In critical domains (e.g., oil and gas), poor quality and low efficient services provided by CPSs (e.g., subsea production systems) will cause severe issues (e.g., oil or gas leaks to the sea). In this project, we aim to improve the quality and productivity of configuring large-scale CPSs. Correctly configured products in CPSs are often directly deployable and operational systems. The method we take is to apply Model Based Engineering (MBE) technologies to automate the configuration process of Product Line Engineering (PLE) to the maximum extent. Effectiveness of a PLE approach for CPSs is characterised by its support for abstraction and automation. Abstraction plays a central role in software reuse, which is required to capture all relevant information in a concise and expressive manner to support automated configuration of products. Automation is required for effective selection and customisation of reusable components. We will propose in this project an interactive and optimal configuration solution (with tool support named as Zen-Configurator) with three key functionalities implemented: Decision Inference, Decision Ordering and Consistency Checking. In literature, it does not exist a configuration solution that supports all these functionalities in an integrated manner with a user acceptable performance. To address this R&D challenge, we will base our solution on the theoretical foundation including: 1) cost-effective optimisation for supporting decision ordering, 2) optimised constraint solving to enable decision inference, 3) effective formalisation of consistency checking, and 4) novel algorithms to enable the three functionalities with user acceptable performance.
Project leader: Tao Yue
Category: Øvrige forskningsinstitutter
Institution: SIMULA RESEARCH LABORATORY AS