Is Self-Admitted Technical Debt a Good Indicator of Architectural Divergences?

Sierra, Giancarlo; Tahmid, Ahmad; Shihab, Emad; Tsantalis, Nikolaos

doi:10.1109/saner.2019.8667999

Cited by 9 publications

(3 citation statements)

References 12 publications

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“…One important threat can be represented by mistakes in the used dataset, in terms of both SATD presence and introduction, removal occurrence and removal strategy. As explained in Section II, we mitigated this problem by using a dataset of SATD occurrences used in different research works [9], [44]. Concerning the removal strategies, these have been addressed by multiple evaluators, as the paper proposing the removal taxonomy has explained [58].…”

Section: B Threats To Validitymentioning

confidence: 99%

Automatically Learning Patterns for Self-Admitted Technical Debt Removal

Zampetti

Serebrenik

Penta

2020

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

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Section: B Threats To Validitymentioning

confidence: 99%

Automatically Learning Patterns for Self-Admitted Technical Debt Removal

Zampetti

Serebrenik

Penta

2020

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

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“…Sierra et al [25] investigate the possibility of using source code comments that indicate technical debt to resolve architectural divergences. The authors used a dataset of previously classified SATD comments to trace architectural divergences in an open-source system.…”

Section: Related Workmentioning

confidence: 99%

Beyond the Code: Mining Self-Admitted Technical Debt in Issue Tracker Systems

Xavier,

Ferreira,

Brito

et al. 2020

Preprint

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Self-admitted technical debt (SATD) is a particular case of Technical Debt (TD) where developers explicitly acknowledge their suboptimal implementation decisions. Previous studies mine SATD by searching for specific TD-related terms in source code comments. By contrast, in this paper we argue that developers can admit technical debt by other means, e.g., by creating issues in tracking systems and labelling them as referring to TD. We refer to this type of SATD as issue-based SATD or just SATD-I. We study a sample of 286 SATD-I instances collected from five open source projects, including Microsoft Visual Studio and GitLab Community Edition. We show that only 29% of the studied SATD-I instances can be tracked to source code comments. We also show that SATD-I issues take more time to be closed, compared to other issues, although they are not more complex in terms of code churn. Besides, in 45% of the studied issues TD was introduced to ship earlier, and in almost 60% it refers to Design flaws. Finally, we report that most developers pay SATD-I to reduce its costs or interests (66%). Our findings suggest that there is space for designing novel tools to support technical debt management, particularly tools that encourage developers to create and label issues containing TD concerns.

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“…More recently, other researchers focusing on developing approaches for TD automated documentation or automated suggestions for TD removal [18] must also focus on other actions that change the program's behavior, e.g., changing Application Programming Interfaces or pre and post conditions. In [19], the authors investigate the possibility of using SATD comments to resolve architectural divergences. They leverage a dataset of previously classified SATD comments to trace them to the architectural divergences of a large open source system, namely ArgoUML.…”

Section: Investigation Of Effects On Satd and Quality Metricsmentioning

confidence: 99%