An approach for decision support on the uncertainty in feature model evolution

Software systems could be seen as a hierarchy of features which are evolving due to the dynamic of the working environments. The companies who build software thus need to make an appropriate strategy, which takes into consideration of such dynamic, to select features to be implemented. In this work, we propose an approach to facilitate such selection by providing a means to capture the uncertainty of evolution in feature models. We also provide two analyses to support the decision makers. The approach is exemplified in the Smart Grid scenario.