A feature model for model-to-text transformation languages

Model-to-text (M2T) transformation is an important model management operation, as it is used to implement code and documentation generation; model serialisation (enabling model interchange); and model visualisation and exploration. Despite the creation of the MOF Model-To-Text Transformation Language (MOFM2T) in 2008, many very different M2T languages exist today. Because there is little interoperability between M2T languages and rewriting an existing M2T transformation in a new language is costly, developers face a difficult choice when selecting a M2T language. In this paper, we use domain analysis to identify a preliminary feature model for M2T languages. We demonstrate the appropriateness of the feature model by describing two different M2T languages, and discuss potential applications for a tool-supported and model-driven approach to describing the features of M2T languages.