Towards system analysis with variability model metrics

Variability models are central artifacts in highly configurable systems. They aim at planning, developing, and configuring systems by describing configuration knowledge at different levels of formality. The existence of large models using a variety of modeling concepts in heterogeneous languages with intricate semantics calls for a unified measuring approach. In this position paper, we attempt to take a first step towards such a measurement. We discuss perspectives of metrics, define low-level measurement goals, and conceive and implement metrics based on variability modeling concepts found in real-world languages and models. An evaluation of these metrics with real-world models and codebases provides insight into the benefits of such metrics for the defined perspectives.