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
problem. 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 an then we evaluated two of
them, which aim at identification of self-admitted technical debt. Thy are named eXcomment e DebtHunter. Results:
We found 92 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 find 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 o debt
present in the system under evaluation.