research-article

An empirical study on self-fixed technical debt

Authors:

Daniel Feitosa,

Paris AvgeriouAuthors Info & Claims

TechDebt '20: Proceedings of the 3rd International Conference on Technical Debt

Pages 11 - 20

https://doi.org/10.1145/3387906.3388621

Published: 25 September 2020 Publication History

Abstract

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.

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Cited By

Silva LSantos I(2024)A Catalog of Prevention Strategies for Test Technical DebtProceedings of the XXIII Brazilian Symposium on Software Quality10.1145/3701625.3701692(706-717)Online publication date: 5-Nov-2024
https://dl.acm.org/doi/10.1145/3701625.3701692
Tan JFeitosa DAvgeriou P(2023)The lifecycle of Technical Debt that manifests in both source code and issue trackersInformation and Software Technology10.1016/j.infsof.2023.107216159:COnline publication date: 10-May-2023
https://dl.acm.org/doi/10.1016/j.infsof.2023.107216
Alfayez RWinn RAlwehaibi WVenson EBoehm B(2023)How SonarQube-identified technical debt is prioritizedInformation and Software Technology10.1016/j.infsof.2023.107147156:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.infsof.2023.107147
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Index Terms

An empirical study on self-fixed technical debt
1. Software and its engineering
  1. Software creation and management
    1. Software development process management

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cover image ACM Conferences

TechDebt '20: Proceedings of the 3rd International Conference on Technical Debt

June 2020

131 pages

ISBN:9781450379601

DOI:10.1145/3387906

General Chair:
Clemente Izurieta
Montana State University
,
Program Chairs:
Matthias Galster
University of Canterbury
,
Michael Felderer
University of Innsbruck

Copyright © 2020 ACM.

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Published: 25 September 2020

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TechDebt '20: International Conference on Technical Debt

June 28 - 30, 2020

Seoul, Republic of Korea

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TechDebt '20 Paper Acceptance Rate 14 of 31 submissions, 45%;

Overall Acceptance Rate 14 of 31 submissions, 45%

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Cited By

Silva LSantos I(2024)A Catalog of Prevention Strategies for Test Technical DebtProceedings of the XXIII Brazilian Symposium on Software Quality10.1145/3701625.3701692(706-717)Online publication date: 5-Nov-2024
https://dl.acm.org/doi/10.1145/3701625.3701692
Tan JFeitosa DAvgeriou P(2023)The lifecycle of Technical Debt that manifests in both source code and issue trackersInformation and Software Technology10.1016/j.infsof.2023.107216159:COnline publication date: 10-May-2023
https://dl.acm.org/doi/10.1016/j.infsof.2023.107216
Alfayez RWinn RAlwehaibi WVenson EBoehm B(2023)How SonarQube-identified technical debt is prioritizedInformation and Software Technology10.1016/j.infsof.2023.107147156:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.infsof.2023.107147
Rantala LMäntylä MLenarduzzi V(2023)Keyword-labeled self-admitted technical debt and static code analysis have significant relationship but limited overlapSoftware Quality Journal10.1007/s11219-023-09655-z32:2(391-429)Online publication date: 16-Nov-2023
https://doi.org/10.1007/s11219-023-09655-z
Santamaria ILarrucea XFernandez‐Gauna B(2023)Integrating privacy debt and VSE's software developmentsJournal of Software: Evolution and Process10.1002/smr.243735:8Online publication date: 7-Aug-2023
https://dl.acm.org/doi/10.1002/smr.2437
Pavlič LHliš THeričko MBeranič T(2022)The Gap between the Admitted and the Measured Technical Debt: An Empirical StudyApplied Sciences10.3390/app1215748212:15(7482)Online publication date: 26-Jul-2022
https://doi.org/10.3390/app12157482
Szabados KFarkas IKovács A(2022)Reproducibility in the technical debt domainActa Universitatis Sapientiae, Informatica10.2478/ausi-2021-001613:2(335-360)Online publication date: 2-Feb-2022
https://doi.org/10.2478/ausi-2021-0016
TAN JPANG JLIU C(2022)What Factors Affect the Performance of Software after Migration: A Case Study on Sunway TaihuLight SupercomputerIEICE Transactions on Information and Systems10.1587/transinf.2021MPL0003E105.D:1(26-30)Online publication date: 1-Jan-2022
https://doi.org/10.1587/transinf.2021MPL0003
Forootani SDi Sorbo AVisaggio C(2022)An Exploratory Study on Self-Fixed Software Vulnerabilities in OSS Projects2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER53432.2022.00023(90-100)Online publication date: Mar-2022
https://doi.org/10.1109/SANER53432.2022.00023
Chandramouli PCodabux ZVidoni M(2022)analyzeR: A SonarQube plugin for analyzing object-oriented R PackagesSoftwareX10.1016/j.softx.2022.10111319(101113)Online publication date: Jul-2022
https://doi.org/10.1016/j.softx.2022.101113
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