Impact of footprinting on model quality: An experimental evaluation

When modeling requirements, software analysts have to choose the relevant modeling constructs among all those available. If they do not choose the right set, their model may lack some important information or their model may contain many superfluous details. In previous work, we proposed to capture the purpose of a model with a set of model operations such as queries or model transformations. Then, modelers can analyze the footprints of these operations, that is, the set of model elements touched during their execution. In this paper, we report on two controlled experiments performed with students to evaluate whether footprinting can help them in creating better models. While our studies did not demonstrate statistically significant benefits of footprinting, they reveal the importance of training and tool support for the analysis of footprints.