Kevin Feichtinger, Rick Rabiser,
"Variability Model Transformations: Towards Unifying Variability Modeling"
, in IEEE: Proc. of the 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), IEEE, Washington, Seite(n) 179-182, 2020, ISBN: 978-1-7281-9532-2
Variability Model Transformations: Towards Unifying Variability Modeling
Sprache des Titels:
Proc. of the 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)
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