The paper “Exploring Model-Based Repositories for a Broad Range of Industrial Applications and Challenges” has been accepted to The 14th International Conference on Quality Software, organised in Dallas, USA, October 2-3. Co-authored by several Certus partners, the paper demonstrates how leading expertise from user partners and academia can come together to address key industrial challenges. The main authors from Simula´s side are Tao Yue and Shaukat Ali, and the co-authors come from a long range of companies: Kongsberg Maritime, FMC Technologies, Cisco Systems of Norway, Akerhus University Hospital, The Cancer Registry of Norway, and Attensi.
Nowadays, systems are becoming increasingly complex and large and the process of developing such large-scale systems is becoming complicated with high cost and enormous effort required. Such a complicated process has a prominent challenge to ensure the quality of delivered artifacts. Therefore, there is clearly a need to facilitate reuse of developed artifacts (e.g., requirements, architecture, tests) and enable automated analyses such as risk analysis, prioritizing test cases, change impact analysis, with the objective to reduce cost, effort and improve quality. Model-based engineering provides a promising mechanism to facilitate reuse and enable automation. The key idea is to use models as the backbone of structuring repositories that contain reusable artifacts (e.g., test cases, requirements). Such a backbone model is subsequently used to enable various types of automation such as model-based testing and automated rule verification. In this pa-per, we report 12 industrial projects from five different industry domains that all require the construction of model-based repositories to enable various types of automation. We believe using models as the backbone to structure repositories for the purpose of enabling different types of automation in different contexts is a new and non-conventional model-based development research approach. This exploratory paper will serve the basis for future research to derive a generic model-based repository.