Mapping Features to Models: A Template Approach Based on Superimposed Variants

Although a feature model can represent commonalities and variabilities
in a very concise taxonomic form, features in a feature model are
merely symbols. Mapping features to other models, such as behavioral
or data specifications, gives them semantics. In this paper, we
propose a general template-based approach for mapping feature models
to concise representations of variability in different kinds of other
models. We show how the approach can be applied to UML 2.0 activity
and class models and describe a prototype implementation.