Widespread adoption of Model-Driven Engineering (MDE) in industrial contexts, especially in large companies, leads to an abundance of MDE artifacts such as Domain-Specific Languages and models. ASML is an example of such a company where multidisciplinary teams work on various ecosystems with many languages and models. Automated analyses of those artifacts, e.g., for detecting duplication and cloning, can potentially aid the maintenance and evolution of those ecosystems. In this chapter, we explore a variety of model analytics approaches using our framework SAMOS in the industrial context of ASML ecosystems. We have performed case studies involving clone detection on ASML's data and control models within the ASOME ecosystem, cross-language conceptual analysis and language-level clone detection on three ecosystems, and finally architectural analysis and reconstruction on the CARM2G ecosystem. We discuss how model analytics can be used to discover insights in MDE ecosystems (e.g., via model clone detection and architectural analysis) and opportunities such as refactoring to improve them.
|Title of host publication||Model Management and Analytics for Large Scale Systems|
|Number of pages||44|
|Publication status||Published - 17 Sep 2019|