The project LEA-xDSML - Language Engineering for Analyzable Executable Domain-Specific Modeling Languages resides in the context of Model-Driven Engineering (MDE), which proposes the use of domain-specific modeling languages (DSMLs) to reduce the complexity.


LEA xDSML is a research project concerned with language engineering methods for executable modeling languages. This project started in July 2018 at TU Wien and was moved in January 2019 to JKU Linz. Currently, it is carried out by the Software Engineering Department at JKU and funded by the Austrian Science Fund FWF. This project will run for three years.

Context
LEA xDSML resides in the context of Model-Driven Engineering (MDE), which proposes the use of domain-specific modeling languages (DSMLs) to reduce the complexity associated with the development of complex software-intensive systems, as, for instance, found in the automation domain, production domain, and automotive domain.

DSMLs are increasingly being developed to continuously leverage the domain-specific expertise of the various stakeholders involved in the development of complex system. Thereby, the integration of domain-specific knowledge into DSMLs can significantly improve the productivity of the development process and the quality of the final system. However, the development of DSMLs has also been recognized as a challenging and significant software engineering task itself.

This project is maintained by jku win-se

Duration
01/2019-12/2022

Partners
Johannes Kepler University Linz,
Institute of Telecooperation

LeaxDSML website

Contact
Manuel Wimmer
Luca Berardinelli

LEAxDSML: Language Engineering for Analyzable Executable DSMLs

Publications

D. Bork, K. Anagnostou, M. Wimmer: Towards Interoperable Metamodeling Platforms: The Case of Bridging ADOxx and EMF, In: Franch, X., Poels, G., Gailly, F., Snoeck, M. (eds) in 34th International Conference on Advanced Information Systems Engineering, CAiSE 2022, Leuven, Belgium, June 6-10, 2022, Lecture Notes in Computer Science, Volume 13295, Springer Cham, pages 479-497. Doi: 10.1007/978-3-031-07472-1_28
Conference Article