An Empirical Study of the Impact of Developer Proficiency on Bug fixing Efficiency and Accuracy

Hissan, Khairatun; Hasan, Adiba; Sananda, Fatema-tuz-Zohora

dc.contributor.author	Hissan, Khairatun
dc.contributor.author	Hasan, Adiba
dc.contributor.author	Sananda, Fatema-tuz-Zohora
dc.date.accessioned	2024-01-18T08:11:30Z
dc.date.available	2024-01-18T08:11:30Z
dc.date.issued	2023-05-30
dc.identifier.citation	[1] S. Kalvala and R. Warburton, “A formal approach to fixing bugs,” 09 2011, pp. 172–187. [2] C. Wang, Y. Li, L. Chen, W. Huang, Y. Zhou, and B. Xu, “Examining the effects of developer familiarity on bug fixing,” Journal of Systems and Software, vol. 169, p. 110667, 2020. [3] A. Yadav, S. K. Singh, and J. S. Suri, “Ranking of software developers based on expertise score for bug triaging,” Information and Software Technology, vol. 112, pp. 1–17, 2019. [4] V. R. Basili and B. T. Perricone, “Software errors and complexity: an empirical investigation0,” Communications of the ACM, vol. 27, no. 1, pp. 42–52, 1984. [5] A. Radu and S. Nadi, “A dataset of non-functional bugs,” in 2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR). IEEE, 2019, pp. 399–403. [6] D. J. Dean, H. Nguyen, X. Gu, H. Zhang, J. Rhee, N. Arora, and G. Jiang, “Perf scope: Practical online server performance bug inference in production cloud computing infrastructures,” in Proceedings of the ACM Symposium on Cloud Computing, 2014, pp. 1–13. [7] A. B. Sánchez, P. Delgado-Pérez, I. Medina-Bulo, and S. Segura, “Tandem: A taxonomy and a dataset of real-world performance bugs,” IEEE Access, vol. 8, pp. 107 214–107 228, 2020. [8] A. Khatun and K. Sakib, “A bug assignment approach combining expertise and recency of both bug fixing and source commits.” in ENASE, 2018, pp. 351–358. [9] C. Weiss, R. Premraj, T. Zimmermann, and A. Zeller, “How long will it take to fix this bug?” in Fourth International Workshop on Mining Software Repositories (MSR’07: ICSE Workshops 2007). IEEE, 2007, pp. 1–1. 40 [10] S. A. Licorish and S. G. MacDonell, “Exploring software developers’ work prac tices: Task differences, participation, engagement, and speed of task resolution,” Information & Management, vol. 54, no. 3, pp. 364–382, 2017. [11] H. Shafiq and z. Arshad, “Automated debugging and bug fixing solutions: A systematic literature review and classification,” Ph.D. dissertation, 11 2014. [12] C. Bird, N. Nagappan, B. Murphy, H. Gall, and P. Devanbu, “Don’t touch my code! examining the effects of ownership on software quality,” in Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering, 2011, pp. 4–14. [13] M. Cataldo, P. A. Wagstrom, J. D. Herbsleb, and K. M. Carley, “Identification of coordination requirements: Implications for the design of collaboration and awareness tools,” in Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work, 2006, pp. 353–362. [14] N. Nagappan, B. Murphy, and V. Basili, “The influence of organizational struc ture on software quality: an empirical case study,” in Proceedings of the 30th international conference on Software engineering, 2008, pp. 521–530. [15] F. P. Brooks Jr, The mythical man-month: essays on software engineering. Pear son Education, 1995. [16] B. Curtis, H. Krasner, and N. Iscoe, “A field study of the software design process for large systems,” Communications of the ACM, vol. 31, no. 11, pp. 1268–1287, 1988. [17] A. Espinosa, R. Kraut, J. Lerch, S. Slaughter, J. Herbsleb, and A. Mockus, “Shared mental models and coordination in large-scale, distributed software de velopment,” 2001. [18] S. Zaman, B. Adams, and A. E. Hassan, “Security versus performance bugs: a case study on firefox,” in Proceedings of the 8th working conference on mining software repositories, 2011, pp. 93–102. [19] J. Imseis, C. Nachuma, S. Arifuzzaman, M. Zibran, and Z. A. Bhuiyan, “On the assessment of security and performance bugs in chromium open-source project,” in International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications. Springer, 2019, pp. 145–157. [20] L. D. Panjer, “Predicting eclipse bug lifetimes,” in Fourth international workshop on mining software repositories (MSR’07: ICSE workshops 2007). IEEE, 2007, pp. 29–29. [21] H. Zeng and D. Rine, “Estimation of software defects fix effort using neural net works,” in Proceedings of the 28th Annual International Computer Software and 41 Applications Conference, 2004. COMPSAC 2004., vol. 2. IEEE, 2004, pp. 20– 21. [22] L. Marks, Y. Zou, and A. E. Hassan, “Studying the fix-time for bugs in large open source projects,” in Proceedings of the 7th International Conference on Predictive Models in Software Engineering, 2011, pp. 1–8. [23] Q. Song, M. Shepperd, M. Cartwright, and C. Mair, “Software defect association mining and defect correction effort prediction,” IEEE Transactions on Software Engineering, vol. 32, no. 2, pp. 69–82, 2006. [24] J. Han, M. Kamber, and J. Pei, “2 - getting to know your data,” in Data Mining (Third Edition), third edition ed., ser. The Morgan Kaufmann Series in Data Management Systems, J. Han, M. Kamber, and J. Pei, Eds. Boston: Morgan Kaufmann, 2012, pp. 39–82. [Online]. Available: https://www.sciencedirect.com/science/article/pii/B9780123814791000022	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/2064
dc.description	Supervised by Mr. Shohel Ahmed, Assistant Professor, Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.description.abstract	In the modern software systems’ evolution, solving bugs efficiently and reducing the life cycle of a bug has become increasingly essential. The developer’s proficiency has a huge impact in this case. So our target is to study the effect of developer’s profi ciency on bug fixing efficiency and accuracy. We conducted an empirical study on a bug repository of an open-source project containing approximately 42574 issues. We proposed six factors, Total number of solved tasks, Mean time to solve a task, Task reopen ratio, Total number of fixed bugs, Mean time to fix a bug, and Bug reopen ratio for calculating developers’ proficiency value. For validating our metric we also im plemented Structural Equation Model (SEM) in our study. The analysis of your data revealed that the selected factors do indeed impact a developer’s proficiency. Addition ally, assigning bugs to proficient developers was found to reduce the bug life cycle. We also observed that, highly proficient developers may not always exhibit a high level of accuracy. Therefore, to effectively reduce the bug life cycle, it is crucial to focus on both the proficiency and accuracy levels of developers	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.title	An Empirical Study of the Impact of Developer Proficiency on Bug fixing Efficiency and Accuracy	en_US
dc.type	Thesis	en_US