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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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Dataset . 2020
License: CC BY
Data sources: ZENODO
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Who (Self) Admits Technical Debt?

Authors: Fucci, Gianmarco; Zampetti, Fiorella; Serebrenik, Alexander; Di Penta, Massimiliano;

Who (Self) Admits Technical Debt?

Abstract

Self-Admitted Technical Debt (SATD) are comments, left by developers in the source code or elsewhere, aimed at describing the presence of TD, i.e., source code "not ready yet''. Although this was never stated in the original paper by Potdar and Shihab, the term SATD might suggest that it refers to a ``self-admission'' by whoever has written or changed the source code. This paper empirically investigates, using a curated SATD dataset from five Java open source projects, (i) the extent to which SATD comments are introduced by authors different from those who have done last changes to the related source code, and (ii) when this happens, what is the level of ownership those developers have about the commented source code. Results of the study indicate that, depending on the project, the percentage of SATD admissions introduced or changed without modifying the related source code varies between 0% and 16%, and therefore represent a small, yet not negligible, phenomenon. The level of ownership of those developers is not particularly low, with a median value per project between 10% and 42%. This indicates the possible use of SATD as a different way to perform code review, although this behavior should be considered sub-optimal to the use of more traditional tools, which entail suitable notification mechanisms. This dataset contains data used to compute the paper's results.

Country
Netherlands
Keywords

Self-admitted technical debt, Code review, Empirical study

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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