Modeling languages, just as all software artifacts, evolve. This poses the risk that legacy
models of a company get lost, when they become incompatible with the new language …

Abstract Model transformations are precious and effortful outcomes of Model-Driven
Engineering. As any other artifact, transformations are also subject to evolution forces. Not …

When a language evolves, meta-models and associated gram-mars need to be co-evolved
to stay mutually consistent. Previous work has supported the automated migration of a …

Smart ecosystems are the drivers of modern society. They control infrastructures of socio-
techno-economic importance, ensuring their stable and sustainable operation. Smart …

Harnessing metamodels to engineer application domains is at the core of Model-Driven
Engineering. A large number of artifacts pursuing a common scope are defined starting from …

In model-driven engineering (MDE), metamodels and domain-specific languages are key
artifacts as they are used to define syntax and static semantics of domain models. However …

Abstract Model-to-model transformations are often employed to establish translational
semantics of Domain-Specific Languages (DSLs) by mapping high-level models into more …

Metamodels evolve even more frequently than programming languages. This evolution
process may result in a large number of instance models that are no longer conforming to …

A domain is an area of knowledge that uses common concepts for describing phenomena,
requirements, problems, capabilities, and solutions. A domain is usually associated with well …

During the whole life-cycle of software-intensive systems in safety-critical domains, system
models must consistently co-evolve with quality evaluation models like fault trees. However …