A learning based approach for green software measurements

Measuring specific software quality requirements in a continuous way and at runtime all along the development processes is crucial. Moreover, considering principles of measurement theory, it is still very complex to integrate green metrics in a common standardized and autonomous framework. In our approach, we propose an automated solution based on continuous analysis of SW green measurements, using at runtime a machine learning algorithm. The method allows to suggest and aid in the decision of the use of new or updated green metrics during the software measurement processes. Experiments are performed on the greentrace datasets.