On the Relationship between Self-Admitted Technical Debt Removals and Technical Debt Measures

被引:11
|
作者
Aversano, Lerina [1 ]
Iammarino, Martina [1 ]
Carapella, Mimmo [1 ]
Del Vecchio, Andrea [1 ]
Nardi, Laura [1 ]
机构
[1] Univ Sannio, Dept Engn, I-82100 Benevento, Italy
关键词
software quality; technical debt; self-admitted technical debt; software maintenance; software evolution; software measures;
D O I
10.3390/a13070168
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The technical debt (TD) in a software project refers to the adoption of an inadequate solution from its design to the source code. When developers admit the presence of technical debt in the source code, through comments or commit messages, it is called self-admitted technical debt (SATD). This aspect of TD has been the subject of numerous research studies, which have investigated its distribution, the impact on software quality, and removal. Therefore, this work focuses on the relationship between SATD and TD values. In particular, the study aims to compare the admitted technical debt with respect to its objective measure. In fact, the trends of TD values during SATD removals have been studied. This was done thanks to the use of an SATD dataset and their related removals in four open source projects. Instead, the SonarQube tool was used to measure TD values. Thanks to this work, it turned out that SATD removals in a few cases correspond to an effective reduction of TD values, while in numerous cases, the classes indicated are removed.
引用
收藏
页数:16
相关论文
共 50 条
  • [31] Deep neural network ensembles for detecting self-admitted technical debt
    Yin, Ming
    Zhu, Kuiyu
    Xiao, Hongli
    Zhu, Dan
    Jiang, Jijiao
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2022, 43 (01) : 93 - 105
  • [32] Quantifying and characterizing clones of self-admitted technical debt in build systems
    Tao Xiao
    Zhili Zeng
    Dong Wang
    Hideaki Hata
    Shane McIntosh
    Kenichi Matsumoto
    Empirical Software Engineering, 2024, 29
  • [33] Correction to: Wait for it: identifying “On-Hold” self-admitted technical debt
    Rungroj Maipradit
    Christoph Treude
    Hideaki Hata
    Kenichi Matsumoto
    Empirical Software Engineering, 2021, 26
  • [34] An Exploratory Study on the Occurrence of Self-Admitted Technical Debt in Android Apps
    Wilder, Gregory, II
    Miyamoto, Riley
    Watson, Samuel
    Kazman, Rick
    Peruma, Anthony
    2023 ACM/IEEE INTERNATIONAL CONFERENCE ON TECHNICAL DEBT, TECHDEBT, 2023, : 1 - 10
  • [35] A Large-Scale Empirical Study on Self-Admitted Technical Debt
    Bavota, Gabriele
    Russo, Barbara
    13TH WORKING CONFERENCE ON MINING SOFTWARE REPOSITORIES (MSR 2016), 2016, : 315 - 326
  • [36] Self-admitted technical debt practices: a comparison between industry and open-source
    Zampetti, Fiorella
    Fucci, Gianmarco
    Serebrenik, Alexander
    Di Penta, Massimiliano
    EMPIRICAL SOFTWARE ENGINEERING, 2021, 26 (06)
  • [37] Quantifying and characterizing clones of self-admitted technical debt in build systems
    Xiao, Tao
    Zeng, Zhili
    Wang, Dong
    Hata, Hideaki
    McIntosh, Shane
    Matsumoto, Kenichi
    EMPIRICAL SOFTWARE ENGINEERING, 2024, 29 (02)
  • [38] An empirical study on self-admitted technical debt in modern code review
    Kashiwa, Yutaro
    Nishikawa, Ryoma
    Kamei, Yasutaka
    Kondo, Masanari
    Shihab, Emad
    Sato, Ryosuke
    Ubayashi, Naoyasu
    INFORMATION AND SOFTWARE TECHNOLOGY, 2022, 146
  • [39] Negativity in self-admitted technical debt: how sentiment influences prioritization
    Cassee, Nathan
    Ernst, Neil
    Novielli, Nicole
    Serebrenik, Alexander
    EMPIRICAL SOFTWARE ENGINEERING, 2025, 30 (02)
  • [40] SATDAUG - A Balanced and Augmented Dataset for Detecting Self-Admitted Technical Debt
    Sutoyo, Edi
    Capiluppi, Andrea
    2024 IEEE/ACM 21ST INTERNATIONAL CONFERENCE ON MINING SOFTWARE REPOSITORIES, MSR, 2024, : 289 - 293