Automated Measurement of Technical Debt: A Systematic Literature Review

Background: Technical Debt (TD) is a quite complex concept that includes several aspect of software development. Often, people talk about TD as the amount of postponed work but this is just a basic approximation of the concept that includes many aspects that are technical and managerial. If TD is managed properly, it can provide a huge advantage but it can also make projects unmaintainable, if not. Therefore, being able of measuring TD is a very important aspect for a proper management of the development process. However, due to the complexity of the concept and the different aspects that are involved, such measurement it not easy and there are several different approaches in literature. Goals: This work aims at investigating the existing approaches to the measurement and the analysis of TD focusing on quantitative methods that could also be automated. Method: The Systematic Literature Review (SLR) approach was applied to 331 studies obtained from the three largest digital libraries and databases. Results: After applying all filtering stages, 21 papers out of 331 were selected and deeply analyzed. The majority of them suggested new approaches to measure TD using different criteria not built on top of existing ones. Conclusions: Existing studies related to the measurement of TD were observed and analyzed. The findings have shown that the field is not mature and there are several models that have almost no independent validation. Moreover few tools for helping to automate the evaluation process exist.