Domain specific languages play an important role in modeldriven engineering of software-intensive industrial systems. A rich body of knowledge exists on the development of languages, modeling environments, and transformation systems. The understanding of architectural choices for combining these parts into a feasible solution, however, is not particularly deep. We report on an endeavor in the realm of a technology transfer process from academia to industry, where we encountered unexpected influences of the architecture on the modeling language. By examining the evolution of our language and its programming interface, we show that these influences mainly stemmed from practical considerations; for identifying these early on, tight interaction between our research lab and the industrial partner was key. In addition, we share insights into the practice of cooperating with industry by presenting essential lessons we learned.
Abstract. Multi-level modeling using so-called clabjects has been proposed as an alternative to UML for modeling domains that feature more than one classification level. In real-world applications, however, this modeling formalism has not yet become popular, because it is a challenge to efficiently represent large models, and providing fast access to all information spread across the metalevels at the same time. In this paper we present the model representation concept that relies on a permanent condensed view of the model, the corresponding traversal algorithms, and their implementations that proved adequate for modeldriven engineering of industrial automation systems consisting of hundreds of thousands of model elements.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.