查看文章

Over the past years, there has been an increase in the application of model driven engineering in industry. Similar to traditional software engineering, understanding how technologies are actually used in practice is essential for developing good tooling, and decision making processes. Unfortunately, obtaining and analyzing empirical data in a model-driven context is still tedious and time consuming, introducing large lead-times. In this paper we present a framework for the automated extraction, analysis, and visualization of data and metrics on model-driven artifacts. We subsequently present various examples of how the framework was successfully applied in a large industrial setting to answer a plethora of different questions with respect to decision making and tool development.