Research interests

  • Empirical Software Engineering
  • Mining Software Repositories
  • Software Engineering
  • Software Quality

Personal webpage

http://www.patanamon.com

Biography

Patanamon is a faculty member of the School of Computing and Information Systems. Her primary research goals are directed towards data-driven software engineering, i.e., uncovering empirical evidence and extracting knowledge from data recorded in software repositories by using statistical analysis. In particular, her research is focused on understanding and improving developer collaboration practices. Her recent research has highlighted the effect that collaboration in software development, such as code reviews, can have on the quality of software products. In addition to the collaboration in the code review processes, the variety of collaboration activities which nowadays can be found in large software repositories have provided opportunities and challenges for software engineering researchers and practitioners. Therefore, she is keen to perform research that (1) incorporates the various types of collaboration activities, (2) glean actionable insights for software engineering management, and (3) provide tool support for software developers in order to improve software quality. Her research has been published in a high impact Software Engineering journal, e.g., the Springer Journal of Empirical Software Engineering (EMSE) and several premier international software engineering conferences like the International Conference on Software Engineering (ICSE), International Conference on Mining Software Repositories (MSR), and International Conference on Software Analysis, Evolution, and Reengineering (SANER).

Recent publications

  1. Ruangwan, S.; Thongtanunam, P.; Ihara, A.; Matsumoto, K. The impact of human factors on the participation decision of reviewers in modern code review. Empirical Software Engineering. Springer Nature. 2019, Vol. 24, Issue 2, pp. 973-1016. DOI: 10.1007/s10664-018-9646-1
  2. Thongtanunam, P.; Shang, W.; Hassan, AE. Will this clone be short-lived? Towards a better understanding of the characteristics of short-lived clones. Empirical Software Engineering. Springer Nature. 2019, Vol. 24, Issue 2, pp. 937-972. DOI: 10.1007/s10664-018-9645-2
  3. Thongtanunam, P.; Mcintosh, S.; Hassan, AE.; Iida, H. Review participation in modern code review: An empirical study of the Android, Qt, and OpenStack projects (journal-first abstract). 2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER). IEEE Explore. 2018, Vol. 2018-March, pp. 475-. DOI: 10.1109/SANER.2018.8330241
  4. Thongtanunam, P.; Mcintosh, S.; Hassan, AE.; Iida, H. Review participation in modern code review: An empirical study of the android, Qt, and OpenStack projects. Empirical Software Engineering. Springer Nature. 2017, Vol. 22, Issue 2, pp. 768-817. DOI: 10.1007/s10664-016-9452-6
  5. Thongtanunam, P.; Mcintosh, S.; Hassan, AE.; Iida, H. Revisiting code ownership and its relationship with software quality in the scope of modern code review. Proceedings of the 38th International Conference on Software Engineering - ICSE '16. Association for Computing Machinery (ACM). 2016, Vol. 14-22-May-2016, pp. 1039-1050. DOI: 10.1145/2884781.2884852
  6. Thongtanunam, P.; Mcintosh, S.; Hassan, AE.; Iida, H. Investigating code review practices in defective files: An empirical study of the Qt system. 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories. IEEE Press. 2015, Vol. 2015-August, pp. 168-179. DOI: 10.1109/MSR.2015.23
  7. Thongtanunam, P.; Tantithamthavorn, C.; Kula, RG.; Yoshida, N.; Iida, H.; Matsumoto, KI. Who should review my code? A file location-based code-reviewer recommendation approach for Modern Code Review. 2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER). IEEE. 2015, pp. 141-150. DOI: 10.1109/SANER.2015.7081824
  8. Pangsakulyanont, T.; Thongtanunam, P.; Port, D.; Iida, H. Assessing MCR discussion usefulness using semantic similarity. 2014 6th International Workshop on Empirical Software Engineering in Practice. IEEE Explore. 2014, pp. 49-54. DOI: 10.1109/IWESEP.2014.11
  9. Thongtanunam, P.; Kula, RG.; Cruz, AEC.; Yoshida, N.; Iida, H. Improving code review effectiveness through reviewer recommendations. Proceedings of the 7th International Workshop on Cooperative and Human Aspects of Software Engineering - CHASE 2014. ACM Press. 2014, pp. 119-122. DOI: 10.1145/2593702.2593705
  10. Thongtanunam, P.; Yang, X.; Yoshida, N.; Kula, RG.; Cruz, AEC.; Fujiwara, K.; Iida, H. REDA: A web-based visualization tool for analyzing modern code review dataset. 2014 IEEE International Conference on Software Maintenance and Evolution. IEEE. 2014, pp. 605-608. DOI: 10.1109/ICSME.2014.106