Model analytics for feature models: case studies for S.P.L.O.T. Repository

Model-Driven Engineering and Software Product Lines promote the use of models as central artifacts for a variety of activities including domain analysis and generative software development. As these paradigms gain popularity, the number and variety of models in use increase. Several initiatives to gather models in repositories exist, such as ATL Zoo for metamodels or S.P.L.O.T. for feature models, aiming for public access and reuse. However, as those repositories are only partly or not at all curated, the growing number of models leads to problems such as duplicates a.k.a. clones, and lack of repository overview. This makes both repository management and model searching/reuse very hard. We address this issue for S.P.L.O.T. by adapting SAMOS, our generic model analytics framework for feature model comparison. We perform two exploratory case studies. First, we aim for getting a high level repository overview with large clusters and their domains. Secondly, we try to get clusters of highly similar models, to be interpreted as duplicates or clones. We conclude our approach is applicable for feature models and can improve the use and maintenance of S.P.L.O.T.