Abstract
In this paper, we illustrate the role of quality assurance in Language-Driven Engineering (LDE) which exploits the observation that the more specific a programming/modeling language is, the better it can be controlled. In fact, well-tailored domain-specific languages (DSLs) allow one to (1) syntactically express a number of semantic properties with the effect that they can be verified during syntax analysis or using more involved static verification techniques like model checking, and (2), combined with a concept of design for testability, to automatically validate run-time properties using, in our case, learning-based testing technology. To ensure practicality and scalability, the LDE approach must be supported by language definition technology, powerful enough to ensure that corresponding Integrated Modeling Environments (IMEs) can be generated on demand. Our LDE ecosystem provides such means in a fashion where the dependencies between the various modeling environments and their corresponding meta-modeling environments are systematically addressed in a path-up/tree-down fashion: application-level requests are stepwise moved up to the meta hierarchy, far enough to fully address the issue at hand. The resulting meta-level changes are then propagated down the meta hierarchy to ensure the adequate migration of all involved IMEs and their corresponding modeled artifacts.
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Bainczyk, A., Boßelmann, S., Krause, M., Krumrey, M., Wirkner, D., Steffen, B. (2022). Towards Continuous Quality Control in the Context of Language-Driven Engineering. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation. Software Engineering. ISoLA 2022. Lecture Notes in Computer Science, vol 13702. Springer, Cham. https://doi.org/10.1007/978-3-031-19756-7_22
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