Research Article
Year 2020,
, 720 - 724, 30.09.2020
Abstract
References
- V. Cosentino, J. Luis, and J. Cabot. Findings from GitHub: methods, datasets and limitations. Proceedings of the 13th International Workshop on Mining Software Repositories, (2016), 137–141.
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- M. L. de L. Júnior, D. M. Soares, A. Plastino, and L. Murta. Automatic assignment of integrators to pull requests: The importance of selecting appropriate attributes. J. Syst. Softw., 144 (2018) 181–196.
- G. Zhao, D. A. da Costa, and Y. Zou. Improving the Pull Requests Review Process Using Learning-to-rank Algorithms. Empir. Softw. Eng., (2019) 1–31.
Year 2020,
, 720 - 724, 30.09.2020
Abstract
In open-source software development environments; textual, numerical, and relationship-based data generated are of interest to researchers. Various data sets are available for this data, which is frequently used in areas such as software engineering and natural language processing. However, since these data sets contain all the data in the environment, the problem arises in the terabytes of data processing. For this reason, almost all of the studies using GitHub data use filtered data according to certain criteria. In this context, using a different data set in each study makes a comparison of the accuracy of the studies quite difficult. In order to solve this problem, a common dataset was created and shared with the researchers, which would allow to work on many software engineering problems.
References
- V. Cosentino, J. Luis, and J. Cabot. Findings from GitHub: methods, datasets and limitations. Proceedings of the 13th International Workshop on Mining Software Repositories, (2016), 137–141.
- V. Cosentino, J. L. Canovas Izquierdo, and J. Cabot. A Systematic Mapping Study of Software Development With GitHub. IEEE Access, 5 (2017) 7173–7192.
- Z. Kotti and D. Spinellis. Standing on shoulders or feet?: the usage of the MSR data papers. Proceedings of the 16th International Conference on Mining Software Repositories, (2019) 565–576.
- G. Gousios. The GHTorrent dataset and tool suite. Proceedings of the 10th Working Conference on Mining Software Repositories, (2013) 233–236.
- Y. Zhang, G. Yin, Y. Yu, and H. Wang. Investigating social media in GitHub’s pull-requests: a case study on Ruby on Rails. Proceedings of the 1st International Workshop on Crowd-based Software Development Methods and Technologies - CrowdSoft 2014 (2014) 37–41.
- E. van der Veen, G. Gousios, and A. Zaidman. Automatically Prioritizing Pull Requests. 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories. (2015) 357–361.
- Y. Yu, H. Wang, V. Filkov, P. Devanbu, and B. Vasilescu. Wait for It: Determinants of Pull Request Evaluation Latency on GitHub. 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories, (2015) 367–371.
- M. L. de L. Júnior, D. M. Soares, A. Plastino, and L. Murta. Automatic assignment of integrators to pull requests: The importance of selecting appropriate attributes. J. Syst. Softw., 144 (2018) 181–196.
- G. Zhao, D. A. da Costa, and Y. Zou. Improving the Pull Requests Review Process Using Learning-to-rank Algorithms. Empir. Softw. Eng., (2019) 1–31.
There are 9 citations in total.
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Engineering Sciences |
| Authors | |
| Publication Date | September 30, 2020 |
| Submission Date | April 29, 2020 |
| Acceptance Date | June 12, 2020 |
| Published in Issue | Year 2020 |