Bridging the gap between academia and industry: transforming the universal variability language to pure::variants and back

Abstract

In the last 30 years, many variability modeling approaches have been developed and new ones are still developed regularly. Most of them are only described in academic papers, only few come with tool support. The sheer plethora of approaches, all differing in terms of scope and expressiveness, makes it difficult to assess their properties, experiment with them and find the right approach for a specific use case. Implementing transformations between variability modeling approaches or importers/exporters for tools can help, but are hard to realize without information loss. In this paper, we describe how we derived and implemented transformations between the academically developed Universal Variability Language and the commercially developed pure::variants tool, with as little information loss as possible. Our approach can also be used to optimize constraints, e.g., reduce their number without an effect on the configuration space, using particular capabilities pure::variants provides. Also, via an existing variability model transformation approach, which uses UVL as a pivot language, we enable the transformation of FeatureIDE feature models, DOPLER decision models, and Orthogonal Variability Models into/from pure::variants and back. With our approach, we work towards bridging the gap between academic and industrial variability modeling tools and enable experiments with the different capabilities these tools provide.