Guest editorial to the special issue on model transformation

Abstract

Models are widespread in systems engineering, and provide a mechanism for managing and controlling complexity when developing large-scale complex IT systems. Models help engineers capture essential information at a suitable level of abstraction, and reason about that information in precise ways. Models are at the heart of model-driven approaches to systems engineering. A key operation in model-driven engineering is model transformation, which is the practice of defining and implementing operations on models. Model transformations refine and/or evolve a model into a different artefact: a new model (e.g., expressed in a different language), an abstraction of the original model, text (e.g., source code), or some other representation needed for a specific domain context. Model transformation approaches are becoming mainstream in model-driven engineering: there are now numerous model transformation languages and tools that allow the specification, implementation, orchestration and execution of transformations, applied to different languages and on different platforms. The research field is extremely active, with substantial research efforts in understanding the advantages and disadvantages of different approaches to model transformation, foundational principles, semantics of transformation languages, and model transformation properties like modularity and composability. There is also substantial interest in treatment of model transformations as reusable assets—