Automatic patch linkage detection in code review using textual content and file location features

A. Bacchelli, C. Bird, Expectations, outcomes, and challenges of modern code review, in: Proceedings of the 35th International Conference on Software Engineering, 2013, pp. 712–721. P.C. Rigby, C. Bird, Convergent contemporary software peer review practices, in: Proceedings of the 9th Joint Meeting on Foundations of Software Engineering, 2013, pp. 202–212. . Android, http://android-review.googlesource.com, 2019. . OpenStack, http://review.openstack.org, 2019. C. Sadowski, L. Söderberg, M. Sipko, A. Bacchelli, Modern code review: A case study at Google, in: Proceedings of the 39th International Conference on Software Engineering: Software Engineering in Practice Track, 2018, pp. 181–190. Baysal, 2016, Investigating technical and non-technical factors influencing modern code review, Empir. Softw. Eng., 93, 2 Rigby, 2014, Peer review on open-source software projects: Parameters, statistical models, and theory, ACM Trans. Softw. Eng. Methodol., 35:1 . Gerrit, http://www.gerritcodereview.com, 2019. . Codestriker, http://codestriker.sourceforge.net, 2019. . ReviewBoard, http://www.reviewboard.org, 2019. Zhang, 2019, Companies’ participation in oss development - an empirical study of openstack, IEEE Trans. Softw. Eng. P.C. Rigby, D.M. German, M.A. Storey, Open source software peer review practices: A case study of the apache server, in: Proceedings of the 30th International Conference on Software Engineering, 2008, pp. 541–550. T. Hirao, S. McIntosh, A. Ihara, K. Matsumoto, The review linkage graph for code review analytics: A recovery approach and empirical study, in: Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2019, pp. 578–589. G. Gousios, M.A. Storey, A. Bacchelli, Work practices and challenges in pull-based development: The contributor’s perspective, in: Proceedings of the 38th International Conference on Software Engineering, 2016, pp. 285–296. Y. Yu, Z. Li, G. Yin, T. Wang, H. Wang, A dataset of duplicate pull-requests in github, in: 2018 IEEE/ACM 15th International Conference on Mining Software Repositories (MSR), 2018, pp. 22–25. Z. Li, G. Yin, Y. Yu, T. Wang, H. Wang, Detecting duplicate pull-requests in github, in: Proceedings of the 9th Asia-Pacific Symposium on Internetware, 2017, 20:1–20:6. L. Ren, S. Zhou, C. Kästner, A. Wa̧sowski, Identifying redundancies in fork-based development, in: 2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER), 2019, pp. 230–241. Q. Wang, B. Xu, X. Xia, T. Wang, S. Li, Duplicate pull request detection: When time matters, in: Proceedings of the 11th Asia-Pacific Symposium on Internetware, 2019, pp. 1–10. X. Yang, R.G. Kula, N. Yoshida, H. Iida, Mining the modern code review repositories: A dataset of people, process and product, in: Proceedings of the 13th International Conference on Mining Software Repositories, 2016, pp. 460–463. S.S. Calculator, https://www.surveysystem.com/sscalc.htm, 2020. H. Hata, C. Treude, R.G. Kula, T. Ishio, 9.6 Million links in source code comments: Purpose, evolution, and decay, in: Proceedings of the 41st International Conference on Software Engineering, 2019, pp. 1211–1221. M. Aniche, C. Treude, I. Steinmacher, I. Wiese, G. Pinto, M.A. Storey, M.A. Gerosa, How modern news aggregators help development communities shape and share knowledge, in: Proceedings of the 40th International Conference on Software Engineering, 2018, pp. 499–510. Viera, 2005, Understanding interobserver agreement: The kappa statistic, Family Med., 36, 0 Mann, 1947, On a test of whether one of two random variables is stochastically larger than the other, Ann. Math. Stat., 5, 0 Cliff, 1996, Answering ordinal questions with ordinal data using ordinal statistics, Multiv. Behav. Res., 33, 1 Breslow, 1970, A generalized Kruskal-Wallis test for comparing K samples subject to unequal patterns of censorship, Biometrika, 57, 9, 10.1093/biomet/57.3.579 Hirao, 2020, Code reviews with divergent review scores: An empirical study of the openstack and qt communities, IEEE Trans. Softw. Eng. F. Ebert, F. Castor, N. Novielli, A. Serebrenik, Confusion in code reviews: reasons, impacts and coping strategies: reasons, impacts, and coping strategies, in: SANER 2019 - Proceedings of the 2019 IEEE 26th International Conference on Software Analysis, Evolution, and Reengineering, Institute of Electrical and Electronics Engineers, 2019, pp. 49–60. Thongtanunam, 2017, Review participation in modern code review, Empir. Softw. Eng., 76, 8 P. Thongtanunam, C. Tantithamthavorn, R.G. Kula, N. Yoshida, H. Iida, K. Matsumoto, Who Should Review My Code? A file location-based code-reviewer recommendation approach for modern code review, in: Proceedings of the 22nd International Conference on Software Analysis, Evolution, and Reengineering, 2015, pp. 141–150. F. Thung, P.S. Kochhar, D. Lo, Dupfinder: Integrated tool support for duplicate bug report detection, in: Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering, 2014, pp. 871–874. J. Ramos, Using tf-idf to determine word relevance in document queries, in: Proceedings of the first Instructional Conference on Machine Learning, 2003, pp. 133–142. Manning, 2008 P. Runeson, M. Alexandersson, O. Nyholm, Detection of duplicate defect reports using natural language processing, in: Proceedings of the 29th International Conference on Software Engineering, 2007, pp. 499–510. Willett, 2006, The porter stemming algorithm: then and now, Program, 21, 9 Yu, 2016, Reviewer recommendation for pull-requests in github, Inf. Softw. Technol., 20, 4 Gusfield, 1997 Kittler, 1998, On combining classifiers, IEEE Trans. Pattern Anal. Mach. Intell., 22, 6 Ranawana, 2006, Multi-classifier systems: Review and a roadmap for developers, Int. J. Hybrid Intell. Syst., 3, 5 A.T. Nguyen, T.T. Nguyen, T.N. Nguyen, D. Lo, C. Sun, Duplicate bug report detection with a combination of information retrieval and topic modeling, in: Proceedings of the 27th International Conference on Automated Software Engineering, 2012, pp. 70–79. M. Ahasanuzzaman, M. Asaduzzaman, C.K. Roy, K.A. Schneider, Mining duplicate questions in stack overflow, in: Proceedings of the 13th International Conference on Mining Software Repositories, 2016, pp. 402–412,. V. Balachandran, Reducing human effort and improving quality in peer code reviews using automatic static analysis and reviewer recommendation, in: Proceedings of the 2013 International Conference on Software Engineering, 2013, pp. 931–940. D. Ma, D. Schuler, T. Zimmermann, J. Sillito, Expert recommendation with usage expertise, in: 2009 IEEE International Conference on Software Maintenance, 2009, pp. 535–538. Lanubile, 2013, Group awareness in global software engineering, IEEE Softw., 1, 8 Fagan, 1976, Design and code inspections to reduce errors in program development, IBM Syst. J., 18, 2 L. Brothers, V. Sembugamoorthy, M. Muller, Icicle: Groupware for code inspection, in: Proceedings of the 1990 ACM Conference on Computer-Supported Cooperative Work, 1990, pp. 169–181. Mashayekhi, 1993, Distributed, collaborative software inspection, IEEE Softw., 66, 10.1109/52.232404 J. Gintell, J. Arnold, M. Houde, J. Kruszelnicki, R. McKenney, G. Memmi, Scrutiny: A collaborative inspection and review system, in: Sommerville, I., Paul, M. (Eds.), Proceedings of the 4th European Software Engineering Conference, 1993, pp. 344–360. J.M. Perpich, D.E. Perry, A.A. Porter, L.G. Votta, M.W. Wade, Anywhere, anytime code inspections: Using the web to remove inspection bottlenecks in large-scale software development, in: Proceedings of the 19th International Conference on Software Engineering, 1997, pp. 14–21. Rigby, 2012, Contemporary peer review in action: Lessons from open source development, IEEE Softw., 5, 6 A. Bosu, M. Greiler, C. Bird, Characteristics of useful code reviews: An empirical study at microsoft, in: Proceedings of the 12th Working Conference on Mining Software Repositories, 2015, pp. 146–156. M. Mukadam, C. Bird, P.C. Rigby, Gerrit software code review data from android, in: Proceedings of the 10th Working Conference on Mining Software Repositories, 2013, pp. 45–48. G. Gousios, M. Pinzger, A. v. Deursen, An exploratory study of the pull-based software development model, in: Proceedings of the 36th International Conference on Software Engineering, 2014, pp. 345–355. X. Zhang, Y. Chen, W.Z. Yongfeng Gu, X. Xie, X. Jia, J. Xuan, How do multiple pull requests change the same code: A study of competing pull requests in GitHub, in: Proceedings of the 34th International Conference on Software Maintenance and Evolution, 2018, pp. 228–239. T. Baum, K. Leßmann, The choice of code review process: A survey on the state of the practice, in: Felderer, M., Méndez Fernández, D., Turhan, B., Kalinowski, M., Sarro, F., Winkler, D. (Eds.), Product-Focused Software Process Improvement, 2017, pp. 111–127. N. Bettenburg, R. Premraj, T. Zimmermann, Sunghun Kim, Duplicate bug reports considered harmful …really?, in: 2008 IEEE International Conference on Software Maintenance, 2008, pp. 337–345. X. Wang, L. Zhang, T. Xie, J. Anvik, J. Sun, An approach to detecting duplicate bug reports using natural language and execution information, in: 2008 ACM/IEEE 30th International Conference on Software Engineering, 2008, pp. 461–470. C. Sun, D. Lo, S. Khoo, J. Jiang, Towards more accurate retrieval of duplicate bug reports, in: 2011 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011), 2011, pp. 253–262.