Recommending Model Refactoring Rules from Refactoring Examples

Models, like other first-class artifacts such as source code, are maintained and may be refactored to improve their quality and, consequently, one of the derived artifacts. Considering the size of the manipulated models, automatic support is necessary for refactoring tasks. When the refactoring rules are known, such a support is simply the implementation of these rules in editors. However, for less popular and proprietary modeling languages, refactoring rules are generally difficult to define. Nevertheless, their knowledge is often embedded in practical examples. In this paper, we propose an approach to recommend refactoring rules that we lean automatically from refactoring examples. The evaluation of our approach on three modeling languages shows that, in general, the learned rules are accurate.