Predicting Which Pull Requests Will Get Reopened in GitHub
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Jing Jiang | Ahmed Ktob | Li Zhang | Abdillah Mohamed | Jing Jiang | Li Zhang | Abdillah Mohamed | Ahmed Ktob
[1] Ken-ichi Matsumoto,et al. Predicting Re-opened Bugs: A Case Study on the Eclipse Project , 2010, 2010 17th Working Conference on Reverse Engineering.
[2] Dietmar Pfahl,et al. Using Dynamic and Contextual Features to Predict Issue Lifetime in GitHub Projects , 2016, 2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR).
[3] Premkumar T. Devanbu,et al. Quality and productivity outcomes relating to continuous integration in GitHub , 2015, ESEC/SIGSOFT FSE.
[4] Shane McKee,et al. Software Practitioner Perspectives on Merge Conflicts and Resolutions , 2017, 2017 IEEE International Conference on Software Maintenance and Evolution (ICSME).
[5] David Lo,et al. A Comparative Study of Supervised Learning Algorithms for Re-opened Bug Prediction , 2013, CSMR 2013.
[6] David Lo,et al. Understanding inactive yet available assignees in GitHub , 2017, Inf. Softw. Technol..
[7] Audris Mockus,et al. Effectiveness of code contribution: from patch-based to pull-request-based tools , 2016, SIGSOFT FSE.
[8] James D. Herbsleb,et al. Social coding in GitHub: transparency and collaboration in an open software repository , 2012, CSCW.
[9] Matthew A. Russell,et al. Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More , 2018 .
[10] Jia-Huan He,et al. Who should comment on this pull request? Analyzing attributes for more accurate commenter recommendation in pull-based development , 2017, Inf. Softw. Technol..
[11] Gang Yin,et al. Reviewer Recommender of Pull-Requests in GitHub , 2014, 2014 IEEE International Conference on Software Maintenance and Evolution.
[12] Jia-Huan He,et al. CoreDevRec: Automatic Core Member Recommendation for Contribution Evaluation , 2015, Journal of Computer Science and Technology.
[13] Jiawei Han,et al. Data Mining: Concepts and Techniques , 2000 .
[14] Foutse Khomh,et al. Supplementary Bug Fixes vs. Re-opened Bugs , 2014, 2014 IEEE 14th International Working Conference on Source Code Analysis and Manipulation.
[15] James D. Herbsleb,et al. Influence of social and technical factors for evaluating contribution in GitHub , 2014, ICSE.
[16] David Lo,et al. Automatic, high accuracy prediction of reopened bugs , 2014, Automated Software Engineering.
[17] Xiaoguang Mao,et al. An Empirical Study on Interaction Factors Influencing Bug Reopenings , 2014, 2014 21st Asia-Pacific Software Engineering Conference.
[18] Ken-ichi Matsumoto,et al. Studying re-opened bugs in open source software , 2012, Empirical Software Engineering.
[19] David Lo,et al. Accurate developer recommendation for bug resolution , 2013, 2013 20th Working Conference on Reverse Engineering (WCRE).
[20] Philip J. Guo,et al. Characterizing and predicting which bugs get reopened , 2012, 2012 34th International Conference on Software Engineering (ICSE).
[21] Georgios Gousios,et al. Work practices and challenges in pull-based development: the contributor's perspective , 2015, ICSE.
[22] Arie van Deursen,et al. An exploratory study of the pull-based software development model , 2014, ICSE.
[23] Jacky W. Keung,et al. An empirical analysis of reopened bugs based on open source projects , 2016, EASE.
[24] Georgios Gousios,et al. Work Practices and Challenges in Pull-Based Development: The Integrator's Perspective , 2014, ICSE.
[25] Aditya K. Ghose,et al. Predicting the delay of issues with due dates in software projects , 2017, Empirical Software Engineering.