An Empirical Study on Factors Impacting Bug Fixing Time

2012 ◽  
Author(s):  
Feng Zhang ◽  
Foutse Khomh ◽  
Ying Zou ◽  
Ahmed E. Hassan
Keyword(s):  
Empirical Study ◽  
Bug Fixing

scholarly journals An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation

2019 ◽  
Vol 28 (4) ◽  
pp. 1-29 ◽  
Author(s):  
Michele Tufano ◽  
Cody Watson ◽  
Gabriele Bavota ◽  
Massimiliano Di Penta ◽  
Martin White ◽  
...  
Keyword(s):  
Empirical Study ◽  
Machine Translation ◽  
Neural Machine Translation ◽  
Bug Fixing ◽  
In The Wild

Comparing Software Bugs in Clone and Non-clone Code: An Empirical Study

2017 ◽  
Vol 27 (09n10) ◽  
pp. 1507-1527
Author(s):  
Judith F. Islam ◽  
Manishankar Mondal ◽  
Chanchal K. Roy ◽  
Kevin A. Schneider
Keyword(s):  
High Risk ◽  
Empirical Study ◽  
Software Development ◽  
Comparative Study ◽  
Software Maintenance ◽  
Statistical Significance ◽  
Ongoing Debate ◽  
Software Bugs ◽  
Bug Fixing

Code cloning is a recurrent operation in everyday software development. Whether it is a good or bad practice is an ongoing debate among researchers and developers for the last few decades. In this paper, we conduct a comparative study on bug-proneness in clone code and non-clone code by analyzing commit logs. According to our inspection of thousands of revisions of seven diverse subject systems, the percentage of changed files due to bug-fix commits is significantly higher in clone code compared with non-clone code. We perform a Mann–Whitney–Wilcoxon (MWW) test to show the statistical significance of our findings. In addition, the possibility of occurrence of severe bugs is higher in clone code than in non-clone code. Bug-fixing changes affecting clone code should be considered more carefully. Finally, our manual investigation shows that clone code containing if-condition and if–else blocks has a high risk of having severing bugs. Changes to such types of clone fragments should be done carefully during software maintenance. According to our findings, clone code appears to be more bug-prone than non-clone code.

scholarly journals An Empirical Study of Bug Fixing Rate

2015 ◽  
Author(s):  
Weiqin Zou ◽  
Xin Xia ◽  
Weiqiang Zhang ◽  
Zhenyu Chen ◽  
David Lo
Keyword(s):  
Empirical Study ◽  
Bug Fixing

Exploration and Exploitation of Developers' Sentimental Variations in Software Engineering

2016 ◽  
Vol 4 (4) ◽  
pp. 35-55 ◽  
Author(s):  
Md Rakibul Islam ◽  
Minhaz F. Zibran
Keyword(s):  
Software Engineering ◽  
Empirical Study ◽  
Software Development ◽  
Open Source ◽  
Emotional Awareness ◽  
Exploration And Exploitation ◽  
Software Artifacts ◽  
Bug Fixing ◽  
Different Types

Software development is highly dependent on human efforts and collaborations, which are immensely affected by emotions. This paper presents a quantitative empirical study of the emotional variations in different types of development activities (e.g., bug-fixing tasks), development periods (i.e., days and times) and in projects of different sizes involving teams of variant sizes. The study also includes an in-depth investigation of emotions' impacts on software artifacts (i.e., commit messages) and exploration of scopes for exploiting emotional variations in software engineering activities. This work is based on careful analyses of emotions in more than 490 thousand commit comments across 50 open-source projects. The findings from this work add to our understanding of the role of emotions in software development, and expose scopes for exploitation of emotional awareness in improved task assignments and collaborations.

Guiding Bug Triage through Developer Analysis in Bug Reports

2016 ◽  
Vol 26 (03) ◽  
pp. 405-431 ◽  
Author(s):  
Tao Zhang ◽  
Geunseok Yang ◽  
Byungjeong Lee ◽  
Alvin T. S. Chan
Keyword(s):  
Empirical Study ◽  
Software Maintenance ◽  
Large Scale ◽  
Software Projects ◽  
Bug Reports ◽  
Bug Fixing ◽  
Bug Report ◽  
Report Analysis ◽  
Mozilla Firefox ◽  
Triage Algorithm

An important part of software maintenance is bug report analysis during bug-fixing, especially for large-scale software projects. Since bugs reported to the bug repository need to be fixed, triagers are responsible to identify appropriate developers to execute the fix. Previous research focused on optimizing this process, such as by duplicate detection and use of developer recommendations for reducing the workload of triagers. However, there were scant studies that analyzed developer roles (e.g. reporter and assignee) in the bug-fixing process. Therefore, in this paper, we perform an in-depth empirical study of the different roles that developers perform in bug resolution. By extracting the factors that affect bug resolution from the analysis results, we propose a novel bug triage algorithm to recommend the appropriate developers to fix a given bug. We implement the proposed recommendations on the Eclipse and Mozilla Firefox projects, with the results showing that the new bug triage algorithm can effectively recommend which experts should fix given bugs.

Are tweets useful in the bug fixing process? An empirical study on Firefox and Chrome

2017 ◽  
Vol 23 (3) ◽  
pp. 1704-1742 ◽  
Author(s):  
Mariam El Mezouar ◽  
Feng Zhang ◽  
Ying Zou
Keyword(s):  
Empirical Study ◽  
Bug Fixing

Exploration and Exploitation of Developers' Sentimental Variations in Software Engineering

2021 ◽  
pp. 1889-1910
Author(s):  
Md Rakibul Islam ◽  
Minhaz F. Zibran
Keyword(s):  
Software Engineering ◽  
Empirical Study ◽  
Software Development ◽  
Open Source ◽  
Emotional Awareness ◽  
Exploration And Exploitation ◽  
Software Artifacts ◽  
Bug Fixing ◽  
Different Types

Software development is highly dependent on human efforts and collaborations, which are immensely affected by emotions. This paper presents a quantitative empirical study of the emotional variations in different types of development activities (e.g., bug-fixing tasks), development periods (i.e., days and times) and in projects of different sizes involving teams of variant sizes. The study also includes an in-depth investigation of emotions' impacts on software artifacts (i.e., commit messages) and exploration of scopes for exploiting emotional variations in software engineering activities. This work is based on careful analyses of emotions in more than 490 thousand commit comments across 50 open-source projects. The findings from this work add to our understanding of the role of emotions in software development, and expose scopes for exploitation of emotional awareness in improved task assignments and collaborations.

Individuals without jobs: An empirical study of job-seeking behavior and reemployment.

1996 ◽  
Vol 81 (1) ◽  
pp. 76-87 ◽  
Author(s):  
Connie R. Wanberg ◽  
John D. Watt ◽  
Deborah J. Rumsey
Keyword(s):  
Empirical Study ◽  
Job Seeking ◽  
Seeking Behavior
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