Extensible and modular abstract syntax for feature modeling based on language constructs

Abstract

Since the definition of feature models in 1990, a large number of language constructs have emerged. Each language construct usually comes with its own abstract and concrete syntax, its semantics, and even its complete language dialect and tool support. Nowadays, there is a consensus in the Software Product Line community about a need for defining a common variability modeling language. But the fact of the matter is that it is very complex to achieve a good compromise between how expressive the language should be and the effort of developing practical tools for a language with all possible language constructs. In this paper, we propose an extensible model-driven engineering approach for defining the abstract syntax of feature modeling language constructs that could be tailored to different needs and domains. We formalize our approach as a set of modular and reusable metamodels that allows practitioners to decide which subset of language constructs to use through: (1) generating a new variability language; and (2) managing feature models with different level of expressiveness. We provide an instantiation and implementation of our approach.