Towards More Relational Feature Models
Arnaud Gotlieb, Dusica Marijan, Sagar Sen · 2015
Feature modeling is of paramount importance to capture variabilities and commonalities within a software product line. Nevertheless, current feature modeling notations are limited, representing only propositional formulae over attributed variables. This position paper advocates the extension of feature modeling formalisms with richer computational domains and relational operations. In particular, it proposes to extend feature modeling with finite and continuous domain variables, with first-order logic quantifiers (∀, ∃), and with N-ary relations between features attributes, and with so-called global constraints. In order to extend the expressiveness while preserving automated analysis facilities, feature models could be semantically interpreted as first-order logic formulae (instead of propositional logic formulae), including global and continuous dependency between features. In simpler words, this paper emphasizes the importance of having more relational feature models and presents next-generation applications.