Splitting Models Using Information Retrieval and Model Crawling Techniques

نویسندگان

  • Daniel Strüber
  • Julia Rubin
  • Gabriele Taentzer
  • Marsha Chechik
چکیده

In team environments, models are often shared and edited by multiple developers. To allow modularity and facilitate developer independence, we consider the problem of splitting a large monolithic model into sub-models. We propose an approach that assists users in incrementally discovering the set of desired sub-models. Our approach is supported by an automated tool that performs model splitting using information retrieval and model crawling techniques. We demonstrate the effectiveness of our approach on a set of real-life case studies, involving UML class models and EMF meta-models.

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تاریخ انتشار 2014