Towards Meaningful Software Metrics Aggregation
Maria Ulan, Welf Löwe, Morgan Ericsson, Anna Wingkvist · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2019
Aggregation of software metrics is a challenging task, it is even more complex when it comes to considering weights to indicate the relative importance of software metrics. These weights are mostly determined manually, it results in subjective quality models, which are hard to interpret. To address this challenge, we propose an automated aggregation approach based on the joint distribution of software metrics. To evaluate the effectiveness of our approach, we conduct an empirical study on maintainability assessment for around 5000 classes from open source software systems written in Java and compare our approach with a classical weighted linear combination approach in the context of maintainability scoring and anomaly detection. The results show that approaches assign similar scores, while our approach is more interpretable, sensitive, and actionable.