An Empirical Study on Self-Fixed Technical Debt

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Technical Debt (TD) can be paid back either by those that incurred it or by others. We call the former self-fixed TD, and it is particularly effective, as developers are experts in their own code and are best-suited to fix the corresponding TD issues. To what extent is TD self-fixed, which types of TD are more likely to be self-fixed and is the remediation time of self-fixed TD shorter than non-self-fixed TD? This paper attempts to answer these questions. It reports on an empirical study that analyzes the self-fixed issues of five types of TD (i.e., Code, Defect, Design, Documentation and Test), captured via static analysis, in more than 17,000 commits from 20 Python projects of the Apache Software Foundation. The results show that more than two thirds of the issues are self-fixed and that the self-fixing rate is negatively correlated with the number of commits, developers and project size. Furthermore, the survival time of self-fixed issues is generally shorter than non-self-fixed issues. Moreover, the majority of Defect Debt tends to be self-fixed and has a shorter survival time, while Test Debt and Design Debt are likely to be fixed by other developers. These results can benefit both researchers and practitioners by aiding the prioritization of TD remediation activities within development teams, and by informing the development of TD management tools.
Original languageEnglish
Title of host publicationProceedings of the 3rd International Conference on Technical Debt (TechDebt '20)
Place of PublicationSeoul, Republic of Korea
PublisherACM Press
Number of pages10
ISBN (Electronic)9781450379601
Publication statusPublished - 28-Jun-2020
Event3rd International Conference on Technical Debt - Seoul, Korea, Republic of
Duration: 28-Jun-202030-Jun-2020
Conference number: 3rd


Conference3rd International Conference on Technical Debt
Abbreviated titleTechDebt 2020
Country/TerritoryKorea, Republic of
Internet address


  • technical debt
  • self-fixed issues
  • Python
  • static analysis

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