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Was self-admitted technical debt removal a real removal?: an in-depth perspective

Authors:

Fiorella Zampetti,

Alexander Serebrenik,

Massimiliano Di PentaAuthors Info & Claims

MSR '18: Proceedings of the 15th International Conference on Mining Software Repositories

Pages 526 - 536

https://doi.org/10.1145/3196398.3196423

Published: 28 May 2018 Publication History

Abstract

Technical Debt (TD) has been defined as "code being not quite right yet", and its presence is often self-admitted by developers through comments. The purpose of such comments is to keep track of TD and appropriately address it when possible. Building on a previous quantitative investigation by Maldonado et al. on the removal of self-admitted technical debt (SATD), in this paper we perform an in-depth quantitative and qualitative study of how SATD is addressed in five Java open source projects. On the one hand, we look at whether SATD is "accidentally" removed, and the extent to which the SATD removal is being documented. We found that that (i) between 20% and 50% of SATD comments are accidentally removed while entire classes or methods are dropped, (ii) 8% of the SATD removal is acknowledged in commit messages, and (iii) while most of the changes addressing SATD require complex source code changes, very often SATD is addressed by specific changes to method calls or conditionals. Our results can be used to better plan TD management or learn patterns for addressing certain kinds of TD and provide recommendations to developers.

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Cited By

Wang HGao ZBi TGrundy JWang XWu MYang X(2024)What Makes a Good TODO Comment?ACM Transactions on Software Engineering and Methodology10.1145/366481133:6(1-30)Online publication date: 28-Jun-2024
https://dl.acm.org/doi/10.1145/3664811
OBrien DBiswas SImtiaz SAbdalkareem RShihab ERajan HRoychoudhury APaiva AAbreu RStorey M(2024)Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub CopilotProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639176(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639176
Wang HGao ZHu XLo DGrundy JWang X(2024)Just-In-Time TODO-Missed Commits DetectionIEEE Transactions on Software Engineering10.1109/TSE.2024.340500550:11(2732-2752)Online publication date: Nov-2024
https://doi.org/10.1109/TSE.2024.3405005
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Index Terms

Was self-admitted technical debt removal a real removal?: an in-depth perspective
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Software evolution

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Published In

cover image ACM Conferences

MSR '18: Proceedings of the 15th International Conference on Mining Software Repositories

May 2018

627 pages

ISBN:9781450357166

DOI:10.1145/3196398

General Chair:
Andy Zaidman
Delft University of Technology, Netherlands
,
Program Chairs:
Yasutaka Kamei
Kyushu University, Japan
,
Emily Hill
Drew University

Copyright © 2018 ACM.

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Published: 28 May 2018

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ICSE '18: 40th International Conference on Software Engineering

May 28 - 29, 2018

Gothenburg, Sweden

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Cited By

Wang HGao ZBi TGrundy JWang XWu MYang X(2024)What Makes a Good TODO Comment?ACM Transactions on Software Engineering and Methodology10.1145/366481133:6(1-30)Online publication date: 28-Jun-2024
https://dl.acm.org/doi/10.1145/3664811
OBrien DBiswas SImtiaz SAbdalkareem RShihab ERajan HRoychoudhury APaiva AAbreu RStorey M(2024)Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub CopilotProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639176(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639176
Wang HGao ZHu XLo DGrundy JWang X(2024)Just-In-Time TODO-Missed Commits DetectionIEEE Transactions on Software Engineering10.1109/TSE.2024.340500550:11(2732-2752)Online publication date: Nov-2024
https://doi.org/10.1109/TSE.2024.3405005
Pinna ALunesu MOrrù STonelli R(2023)Investigation on Self-Admitted Technical Debt in Open-Source Blockchain ProjectsFuture Internet10.3390/fi1507023215:7(232)Online publication date: 30-Jun-2023
https://doi.org/10.3390/fi15070232
Sheikhaei MTian Y(2023)Automated Self-Admitted Technical Debt Tracking at Commit-Level: A Language-independent Approach2023 ACM/IEEE International Conference on Technical Debt (TechDebt)10.1109/TechDebt59074.2023.00009(22-26)Online publication date: May-2023
https://doi.org/10.1109/TechDebt59074.2023.00009
G SR P(2023)Automated Identification and Prioritization of Self-Admitted Technical Debt Using NLP Word Embeddings2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS)10.1109/ICSSAS57918.2023.10331839(963-971)Online publication date: 18-Oct-2023
https://doi.org/10.1109/ICSSAS57918.2023.10331839
Mastropaolo ADi Penta MBavota G(2023)Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We?2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE)10.1109/ASE56229.2023.00103(585-597)Online publication date: 11-Sep-2023
https://doi.org/10.1109/ASE56229.2023.00103
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://dl.acm.org/doi/10.1007/s11219-023-09655-z
Li YSoliman MAvgeriou P(2023)Automatic identification of self-admitted technical debt from four different sourcesEmpirical Software Engineering10.1007/s10664-023-10297-928:3Online publication date: 15-Apr-2023
https://dl.acm.org/doi/10.1007/s10664-023-10297-9
OBrien DBiswas SImtiaz SAbdalkareem RShihab ERajan HRoychoudhury ACadar CKim M(2022)23 shades of self-admitted technical debt: an empirical study on machine learning softwareProceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3540250.3549088(734-746)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3540250.3549088
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