Towards a systematic approach for cognitively efficient configuration visualizations

In Software Product Line Engineering, the configuration process consists in deriving products from a variability model, usually a feature model. Configuration is difficult for stakeholders because of numerous features to choose and complex constraints relating them. If analysis tools assist in getting consistent products, they do not improve the cognitive effort to be carried out by stakeholders. Data visualization techniques are known to be helpful in this respect. However, choosing the right amongst thousands of visualizations available is often done in an ad-hoc way. In this paper, we present a systematic approach which, from a study of the data relevant to the configuration process, leads us to select an appropriate visualization for understanding configuration decisions.