poster

The buggy side of code refactoring: understanding the relationship between refactorings and bugs

Authors:

Rafael de MelloAuthors Info & Claims

ICSE '18: Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings

Pages 406 - 407

https://doi.org/10.1145/3183440.3195030

Published: 27 May 2018 Publication History

Get Access

Abstract

Code refactoring is widely practiced by software developers. There is an explicit assumption that code refactoring improves the structural quality of a software project, thereby also reducing its bug proneness. However, refactoring is often applied with different purposes in practice. Depending on the complexity of certain refactorings, developers might unconsciously make the source code more susceptible to have bugs. In this paper, we present a longitudinal study of 5 Java open source projects, where 20,689 refactorings, and 1,033 bug reports were analyzed. We found that many bugs are introduced in the refactored code as soon as the first immediate change is made on it. Furthermore, code elements affected by refactorings performed in conjunction with other changes are more prone to have bugs than those affected by pure refactorings.

References

[1]

Gabriele Bavota et al. 2012. When does a refactoring induce bugs?. In SCAM.

Digital Library

Google Scholar

[2]

Isabella Ferreira et al. 2018. Research website. (2018). https://isabellavieira57.github.io/icse2018

Google Scholar

[3]

Martin Fowler. 1999. Refactoring. Addison-Wesley Professional.

Google Scholar

[4]

Emerson Murphy-Hill, Chris Parnin, and Andrew P Black. 2012. How we refactor, and how we know it. TSE 38, 1 (2012).

Digital Library

Google Scholar

[5]

F. Palomba et al. 2016. Smells Like Teen Spirit: Improving Bug Prediction Performance Using the Intensity of Code Smells. In ICSME.

Google Scholar

[6]

Jacek Ratzinger, Thomas Sigmund, and Harald C Gall. 2008. On the relation of refactorings and software defect prediction. In MSR.

Digital Library

Google Scholar

[7]

Jacek Śliwerski, Thomas Zimmermann, and Andreas Zeller. 2005. When do changes induce fixes?. In ACM SIGSOFT Software Engineering Notes (SEN). 1--5.

Digital Library

Google Scholar

[8]

Peter Weißgerber and Stephan Diehl. 2006. Are refactorings less error-prone than other changes?. In MSR.

Digital Library

Google Scholar

Cited By

View all

Edward ENyamawe AElisa N(2024)On the Impact of Refactorings on Software Attack SurfaceIEEE Access10.1109/ACCESS.2024.340405812(128570-128584)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3404058
Martins LPontillo VCosta HFerrucci FPalomba FMachado I(2024)Test code refactoring unveiled: where and how does it affect test code quality and effectiveness?Empirical Software Engineering10.1007/s10664-024-10577-y30:1Online publication date: 16-Nov-2024
https://dl.acm.org/doi/10.1007/s10664-024-10577-y
Alexiou MMertoguno J(2023)Automated Binary Program Partitioning through Structural Analysis2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA59645.2023.10345849(1-7)Online publication date: 10-Jul-2023
https://doi.org/10.1109/IISA59645.2023.10345849
Show More Cited By

Index Terms

The buggy side of code refactoring: understanding the relationship between refactorings and bugs

Recommendations

A metric-based approach to identifying refactoring opportunities for merging code clones in a Java software system

A code clone is a code fragment that has other code fragments identical or similar to it in the source code. The presence of code clones is generally regarded as one factor that makes software maintenance more difficult. For example, if a code fragment ...
Prioritising Refactoring Using Code Bad Smells
ICSTW '11: Proceedings of the 2011 IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops

We investigated the relationship between six of Fowler et al.'s Code Bad Smells (Duplicated Code, Data Clumps, Switch Statements, Speculative Generality, Message Chains, and Middle Man) and software faults. In this paper we discuss how our results can ...
An empirical study to improve software security through the application of code refactoring
Abstract Context
Code bad smells indicate design flaws that can degrade the quality of software and can potentially lead to the introduction of faults. They can be eradicated by applying refactoring techniques. Code bad smells that ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

ICSE '18: Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings

May 2018

231 pages

ISBN:9781450356633

DOI:10.1145/3183440

Conference Chair:
Michel Chaudron
Chalmers University of Technology, University of Gothenburg, Sweden
,
General Chair:
Ivica Crnkovic
Chalmers University of Technology, University of Gothenburg, Sweden
,
Program Chairs:
Marsha Chechik
University of Toronto, Canada
,
Mark Harman
Facebook and University College London, United Kingdom

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 May 2018

Check for updates

Author Tags

Qualifiers

Poster

Funding Sources

CAPES/Procad
FAPERJ
CNPq

Conference

ICSE '18

Sponsor:

SIGSOFT
IEEE-CS

ICSE '18: 40th International Conference on Software Engineering

May 27 - June 3, 2018

Gothenburg, Sweden

Acceptance Rates

Overall Acceptance Rate 276 of 1,856 submissions, 15%

Upcoming Conference

ICSE 2025

2025 IEEE/ACM 46th International Conference on Software Engineering

April 26 - May 3, 2025

Ottawa , ON , Canada

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
302
Total Downloads

Downloads (Last 12 months)21
Downloads (Last 6 weeks)2

Reflects downloads up to 29 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Edward ENyamawe AElisa N(2024)On the Impact of Refactorings on Software Attack SurfaceIEEE Access10.1109/ACCESS.2024.340405812(128570-128584)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3404058
Martins LPontillo VCosta HFerrucci FPalomba FMachado I(2024)Test code refactoring unveiled: where and how does it affect test code quality and effectiveness?Empirical Software Engineering10.1007/s10664-024-10577-y30:1Online publication date: 16-Nov-2024
https://dl.acm.org/doi/10.1007/s10664-024-10577-y
Alexiou MMertoguno J(2023)Automated Binary Program Partitioning through Structural Analysis2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA59645.2023.10345849(1-7)Online publication date: 10-Jul-2023
https://doi.org/10.1109/IISA59645.2023.10345849
Bibiano AUchôa AAssunção WTenório DColanzi TVergilio SGarcia A(2023)Composite refactoringInformation and Software Technology10.1016/j.infsof.2022.107134156:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.infsof.2022.107134
Muse BKhomh FAntoniol G(2023)Refactoring practices in the context of data-intensive systemsEmpirical Software Engineering10.1007/s10664-022-10271-x28:2Online publication date: 16-Feb-2023
https://dl.acm.org/doi/10.1007/s10664-022-10271-x
Counsell SNowack VHall TBowes DHaraldsson SWinter EWoodward J(2022)An 80-20 Analysis of Buggy and Non-buggy Refactorings in Open-Source Commits2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA56994.2022.00038(197-200)Online publication date: Aug-2022
https://doi.org/10.1109/SEAA56994.2022.00038
Muse BKhomh FAntoniol G(2022)Do Developers Refactor Data Access Code? An Empirical Study2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER53432.2022.00014(25-35)Online publication date: Mar-2022
https://doi.org/10.1109/SANER53432.2022.00014
Tang YKhatchadourian RBagherzadeh MSingh RStewart ARaja A(2021)An Empirical Study of Refactorings and Technical Debt in Machine Learning SystemsProceedings of the 43rd International Conference on Software Engineering10.1109/ICSE43902.2021.00033(238-250)Online publication date: 22-May-2021
https://dl.acm.org/doi/10.1109/ICSE43902.2021.00033
Bibiano AFernandes EOliveira DGarcia AKalinowski MFonseca BOliveira ROliveira ACedrim D(2019)A Quantitative Study on Characteristics and Effect of Batch Refactoring on Code Smells2019 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)10.1109/ESEM.2019.8870183(1-11)Online publication date: Sep-2019
https://doi.org/10.1109/ESEM.2019.8870183

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

A metric-based approach to identifying refactoring opportunities for merging code clones in a Java software system

Prioritising Refactoring Using Code Bad Smells

An empirical study to improve software security through the application of code refactoring

Comments

Information

Published In

Sponsors

Publisher

Publication History

Check for updates

Author Tags

Qualifiers

Funding Sources

Conference

Acceptance Rates

Upcoming Conference

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations