Variability Model Transformations: Towards Unifying Variability Modeling

Abstract

A plethora of variability modeling approaches has been developed in the last 30 years. Feature modeling and decision modeling became the most common and well-known groups of variability modeling approaches. Even within these groups, however, there are many different variants of approaches. Also, there are many other approaches such as Orthogonal Variability Modeling, UML-based variability modeling, and many more. Despite past and ongoing efforts, there is no standard variability modeling approach the community can agree on. Many approaches have been developed for a certain purpose and have been demonstrated to be useful for at least that purpose, e.g., domain analysis or automated derivation and configuration of products from a software product line. Still, industry frequently develops their own custom variability management solutions. In this short paper, we discuss our first ideas towards developing a framework for variability model transformations. It would allow researchers and practitioners to experiment with and compare different approaches and tools and switch from one approach or tool to another. We demonstrate the basic feasibility of our idea by transforming a feature model into a decision model. We conclude with a research agenda regarding variability model transformations.