Feature models are a widely used modeling notation for variability and commonality management in software product line (SPL) engineering. In order to keep an SPL and its feature model aligned, feature models must be changed by including/excluding new features and products, either because faults in the model are found or to reflect the normal evolution of the SPL. The modification of the feature model to be made to satisfy these change requirements can be complex and error-prone. In this project, we devise a method that is able to automatically update a feature model in order to satisfy a given update request. The method is based on an evolutionary algorithm that iteratively applies structure-preserving mutations to the original model, until the model is completely updated or some other termination condition occurs.
The code is available here https://github.com/fmselab/eafmupdateFor our experiments, we use the feature models in this zip file
The results of our last experiments can be downloaded here