Building Deduplicated Model Repositories to Assess Domain-Specific Languages Evolution
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abstract
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 languageās 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 metamodel/
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.