Using metrics for assessing the quality of ASF+SDF model transformations

Model transformations are an essential part of Model Driven Engineering and are in many ways similar to traditional software artifacts. Therefore it is necessary to define and evaluate the quality of model transformations. We propose a set of six quality attributes to evaluate the quality of model transformations. We define 27 metrics for ASF+SDF model transformations to predict the quality attributes we propose. Metrics data has been collected from six heterogeneous model transformations automatically. The quality of the same transformations has been evaluated manually by several ASF+SDF experts. We assess whether the automatically collected metrics are appropriate predictors for the quality attributes by correlating the metrics data with the expert data. Based on the measurement results, we identify a set of predicting metrics for each of the quality attributes for model transformations. This work has been carried out as part of the FALCON project under the responsibility of the Embedded Systems Institute with Vanderlande Industries as the industrial partner. This project is partially supported by the Netherlands Ministry of Economic Affairs under the Embedded Systems Institute (BSIK03021) program