Mining domain-specific edit operations from model repositories with applications to semantic lifting of model differences and change profiling

Abstract

Model transformations are central to model-driven software development. Applications of model transformations include creating models, handling model co-evolution, model merging, and understanding model evolution. In the past, various (semi-)automatic approaches to derive model transformations from meta-models or from examples have been proposed. These approaches require time-consuming handcrafting or the recording of concrete examples, or they are unable to derive complex transformations. We propose a novel unsupervised approach, called OCKHAM, which is able to learn edit operations from model histories in model repositories. OCKHAM is based on the idea that meaningful domain-specific edit operations are the ones that compress the model differences.