Examining the Impact of Self-Admitted Technical Debt on Software Quality

Wehaibi, Sultan; Shihab, Emad; Guerrouj, Latifa

doi:10.1109/saner.2016.72

“…Wehaibi et al [34] measured the impact of SATD on software development practices nding that the presence of self-admitted technical debt leads to a complex change in the future. From a dierent perspective, Zampetti et al [36] developed a machine learning approach that, by leveraging on structural information (metrics or warnings raised by static analysis tools) is able to recommend developers with design TD to be admitted.…”

Section: Detection and Management Of Technicalmentioning

confidence: 99%

Was self-admitted technical debt removal a real removal?

Zampetti

¹

,

Serebrenik

²

,

Penta

³

2018

Proceedings of the 15th International Conference on Mining Software Repositories

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DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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“…As the prior work showed, not all comments can contain self-admitted technical debt [29], [37]. Therefore, in the preprocessing we exclude the following types of comments:…”

Section: Extracting Source Code Commentsmentioning

confidence: 99%

“…That said, comments that contain task annotations (i.e., "TODO:", "FIXME:", or "XXX:") [36] are not removed since they are usually leveraged by most IDEs, e.g., Eclipse and Netbeans, to automatically generate task lists. • Commented-out source code, which is explicitly commented out by developers and not compiled is also ignored since prior work showed that it generally does not contain self-admitted technical debt [29], [37]. • Automatically generated comments by the IDE are also removed since they, by definition, do not indicate selfadmitted technical debt.…”

Section: Extracting Source Code Commentsmentioning

confidence: 99%

See 1 more Smart Citation

An Empirical Study on the Removal of Self-Admitted Technical Debt

Maldonado

¹

,

Shihab

²

,

Serebrenik

³

2017

2017 IEEE International Conference on Software Maintenance and Evolution (ICSME)

Self Cite

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DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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“…Concerning "how" SATD is being removed, Wehaibi et al [52] found that SATD may lead, in general, towards complex software changes, while Maldonado et al [9] conducted a survey on SATD removal and found that this happens either in the context of bug fixing, or feature addition. Starting from the results of Maldonado et al [9], Zampetti et al [58] analyzed the change patterns that lead towards SATD removal, by combining an automated analysis through GumTree [14] with manual analysis.…”

Section: Introductionmentioning

confidence: 99%

Automatically Learning Patterns for Self-Admitted Technical Debt Removal

Zampetti

¹

,

Serebrenik

²

,

Penta

³

2020

2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)

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DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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Examining the Impact of Self-Admitted Technical Debt on Software Quality

Cited by 100 publications

References 30 publications

Was self-admitted technical debt removal a real removal?

Was self-admitted technical debt removal a real removal?

An Empirical Study on the Removal of Self-Admitted Technical Debt

Automatically Learning Patterns for Self-Admitted Technical Debt Removal

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