A Survey on Incremental Model Transformation Approaches

Steadily evolving models are the heart and soul of Model-Driven Engineering. Consequently, dependent model transformations have to be re-executed to reflect changes in related models, accordingly. In case of frequent, but only marginal changes, the re-execution of complete transformations induces an unnecessary high overhead. To overcome this drawback, incremental model transformation approaches have been proposed in recent years. Since these approaches differ substantially in language coverage, execution, and the imposed overhead, an evaluation and comparison is essential to investigate their strengths and limitations. The contribution of this paper is a dedicated evaluation framework for incremental model transformation approaches and its application to compare a representative subset of recent approaches. Finally, we report on lessons learned to highlight past achievements and future challenges.