Technical Debt Tools: a Survey and an Empirical Evaluation

Background: The life cycle of a technical debt from its identification to its payment is long and may include several activities, such as identification and management. There is a lot of research in the literature to address different sets of these activities by different means. Specifically, several tools have already tackled such technical debt identification problems. However, only a few studies empirically assessed those tools. Method: In this article, we carried a multi-method research. We first surveyed the literature for the technical debt tools available and then we evaluated two of them, which aim at identification of self-admitted technical debt. They are named eXcomment e DebtHunter. Results: We found 97 tools employing different approaches to support technical debt life cycle management. Most of them (59%) address only the high level task of management, instead of actually identify and pay the debt. Additionally, as for our empirical evaluation of tools, our results show that DebtHunter found only 7% of debt identified by eXcomment. In the other way around, eXcomment found 19.9% the debt found by DebtHunter. Besides, both tools have low levels of precision and recall. Conclusion: It is hard to find technical debt through comments. Both tools can find indicators of debt items, however they struggle on the precision and recall. In fact, although eXcomment and DebtHunter diverge on the amount of debt identified, they seem to converge with regard to the type of debt present in the system under evaluation.