An analysis of variability modeling concepts: Expressiveness vs. analyzability

Abstract

Variability modeling is a core activity of software product line engineering. Over the years, many different approaches to variability modeling have been proposed. Typically, the individual approaches have been designed without a detailed justification on why certain modeling concepts should be used. This yields a rather unfunded selection of modeling approaches in practice, e.g., selecting approaches that provide higher modeling concepts than actually needed, but less analyses capabilities than required. Thus, we propose that the focus of an analysis should not be to determine the best modeling language, but rather to provide a characterization on when to use what kind of approach. In particular, the selection of one approach for a specific situation should be driven from the required modeling concepts (expressiveness) and the required analyzability. In this paper, we propose a classification of core concepts of variability modeling based on expressiveness and analyzability. We discuss the methodology for and the classification of variability modeling concepts illustrated by a running example. The contribution of this paper is a modeling approach-independent classification of variability modeling concepts and their dependencies to provide a systematic and rationale basis to anyone designing, standardizing, implementing or selecting a specific variability modeling approach. © 2013 Springer-Verlag Berlin Heidelberg.