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In the scientific community, feature models are the de-facto standard for representing variability in software product line engineering. This is different from industrial settings where they appear to be used much less frequently. We and other authors found that in a number of cases, they lack concision, naturalness and expressiveness. This is confirmed by industrial experience. When modelling variability, an efficient tool for making models intuitive and concise are feature attributes. Yet, the semantics of feature models with attributes is not well understood and most existing notations do not support them at all. Furthermore, the graphical nature of feature models’ syntax also appears to be a barrier to industrial adoption, both psychological and rational. Existing tool support for graphical feature models is lacking or inadequate, and inferior in many regards to tool support for text-based formats. To overcome these …