Building deduplicated model repositories to assess domain-specific languages evolution

Software evolution and maintenance is a real challenge in modern software engineering. In the context of model-driven development, which heavily rely on interconnected (meta-)models, tools and generators, evolving both models and their associated meta-models is particularly complex. This issue is also prevalent in language engineering, where evolving a language's grammar or semantics must remain consistent with the pre-existing models. In this paper, we explore how techniques inspired by repository mining can help a model designer/language engineer to build a deduplicated dataset of existing models available in open source repositories. Deduplication is essential to ensure the evolution made on the meta-model/language can be efficiently assessed. We apply the method to the P4 language, an industrial domain-specific language (Intel, Linux foundation) used to model software defined networks.