A contextualized vocabulary model for identifying technical debt on code comments

The identification of technical debt (TD) is an important step to effectively manage it. In this context, a set of indicators has been used by automated approaches to identify TD items, but some debt may not be directly identified using only metrics collected from the source code. In this work we propose CVM-TD, a model to support the identification of technical debt through code comment analysis. We performed an exploratory study on two large open sources projects with the goal of characterizing the feasibility of the proposed model to support the detection of TD through code comments analysis. The results indicate that (1) developers use the dimensions considered by CVM-TD when writing code comments, (2) CVM-TD provides a vocabulary that may be used to detect TD items, and (3) the proposed model needs to be calibrated in order to reduce the difference between comments returned by the vocabulary and those that may indicate a TD item. Code comments analysis can be used to detect TD in software projects and CVM-TD may support the development team to perform this task.