Published on 09 March 2020
Beyond the Code: Mining Self-Admitted Technical Debt in Issue Tracker Systems
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Self-admitted technical debt (SATD) is a particular case of Technical Debt (TD) where developers explicitly acknowledge their sub-optimal 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.
Citations (9)
- https://doi.org/10.2139/ssrn.4801433OpenAlex
Cited on 01 January 2024
Weight: 1.53
- https://doi.org/10.2139/ssrn.4851040OpenAlex
Cited on 01 January 2024
Weight: 1.53
- https://doi.org/10.2139/ssrn.4160012OpenAlex
Cited on 01 January 2022
Weight: 1.36
- https://doi.org/10.2139/ssrn.4191846OpenAlex
Cited on 01 January 2022
Weight: 1.36
Cited on 08 August 2021
Weight: 1.23
Cited on 01 May 2021
Weight: 1.23
Cited on 08 March 2021
Weight: 1.23
Cited on 11 November 2020
Weight: 1.00
Cited on 01 September 2020
Weight: 1.00
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Publication Details
Subfield
Information Systems
Field
Computer Science
Domain
Physical Sciences
Confidence Score
99%
Source
Open Alex