Systematically Deriving Domain-Specific Transformation Languages

TL;DR

This paper introduces a systematic process to derive domain-specific transformation languages from existing textual modeling language grammars, exemplified by creating CDTrans for UML class diagrams, facilitating easier model transformations.

Contribution

It presents a novel method for deriving transformation languages directly from language grammars, reducing the learning curve for modelers and improving transformation usability.

Findings

Successfully derived CDTrans from UML class diagram grammar

Demonstrated the effectiveness of CDTrans with several refactoring transformations

Simplified the process of creating domain-specific transformation languages

Abstract

Model transformations are helpful to evolve, refactor, refine and maintain models. While domain-specific languages are normally intuitive for modelers, common model transformation approaches (regardless of whether they transform graphical or textual models) are based on the modeling language's abstract syntax requiring the modeler to learn the internal representation of the model to describe transformations. This paper presents a process that allows to systematically derive a textual domainspecific transformation language from the grammar of a given textual modeling language. As example, we apply this systematic derivation to UML class diagrams to obtain a domain-specific transformation language called CDTrans. CDTrans incorporates the concrete syntax of class diagrams which is already familiar to the modeler and extends it with a few transformation operators. To demonstrate the usefulness of the derived transformation language, we describe several refactoring transformations.