Page 60 - 《软件学报》2021年第11期
P. 60
3386 Journal of Software 软件学报 Vol.32, No.11, November 2021
[9] Lipcak J, Rossi B. A large-scale study on source code reviewer recommendation. In: Proc. of the 2018 44th Euromicro Conf. on
Software Engineering and Advanced Applications (SEAA). IEEE, 2018. [doi: 10.1109/SEAA.2018.00068]
[10] Yu Y, Wang H, Yin G, Wang T. Reviewer recommendation for pull-requests in Github: What can we learn from code review and
bug assignment? Information and Software Technology, 2016,74:204−218.
[11] Jiang J, He JH, Chen XY. CoreDevRec: Automatic core member recommendation for contribution evaluation. Journal of Computer
Science and Technology, 2015,30(5):998−1016.
[12] Xia X, Lo D, Wang X, Yang X. Who should review this change? Putting text and file location analyses together for more accurate
recommendations. In: Proc. of the 2015 IEEE Int’l Conf. on Software Maintenance and Evolution (ICSME). IEEE, 2015. 261−270.
[13] Xia Z, Sun H, Jiang J, Wang X, Liu X. A hybrid approach to code reviewer recommendation with collaborative filtering. In: Proc.
of the 2017 6th Int’l Workshop on Software Mining (Software Mining). IEEE, 2017. 24−31.
[14] Yang C, Zhang X, Zeng L, Fan Q, Yin G, Wang H. An empirical study of reviewer recommendation in pull-based development
model. In: Proc. of the 9th Asia-Pacific Symp. on Internetware. ACM, 2017. Article No.14.
[15] https://google.github.io/eng-practices/review/reviewer/speed.html
[16] Rahman MM, Roy CK, Collins JA. Correct: Code reviewer recommendation in Github based on cross-project and technology
experience. In: Proc. of the IEEE/ACM Int’l Conf. on Software Engineering Companion (ICSE-C). IEEE, 2016. 222−231.
[17] Teich J. Pareto-front exploration with uncertain objectives. In: Proc. of the EMO 2001. 2001. 314−328.
[18] Deb K, Agrawal S, Pratap A, Meyarivan T. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization:
NSGA-II. In: Proc. of the PPSN 2000. 2000. 849−858.
[19] Mondal D, Hemmati H, Durocher S. Exploring test suite diversification and code coverage in multi-objective test case selection. In:
Proc. of the ICST 2015. 2015. 1−10.
[20] Yoo S, Harman M. Pareto efficient multi-objective test case selection. In: Proc. of the ISSTA 2007. 2007. 140−150.
[21] Tantithamthavorn C, Teekavanich R, Ihara A, Matsumoto KI. Mining a change history to quickly identify bug locations: A case
study of the eclipse project. In: Proc. of the ISSREW 2013. 2013. 108−113.
[22] Harman M, Mansouri SA, Zhang Y. Search-based software engineering: Trends, techniques and applications. ACM Computing
Surveys (CSUR), 2012,45(1):Article No.11.
[23] Epitropakis MG, Yoo S, Harman M, Burke EK. Empirical evaluation of Pareto efficient multi-objective regression test case
prioritisation. In: Proc. of the ISSTA 2015. 2015. 234−245.
[24] Silva RA, de Souza SDRS, de Souza PSL. A systematic review on search-based mutation testing. Information and Software
Technology, 2017,81:19−35.
[25] Jeong G, Kim S, Zimmermann T. Improving bug triage with bug tossing graphs. In: Proc. of the FSE 2009. 2009. 111−120.
[26] Langdon WB, Harman M, Jia Y. Efficient multi-objective higher order mutation testing with genetic programming. The Journal of
Systems and Software, 2010,83(12):2416−2430.
[27] Rigby PC, German DM, Cowen L, Storey MA. Peer review on open-source software projects: Parameters, statistical models, and
theory. ACM Trans. on Software Engineering and Methodology (TOSEM), 2014,23(4):Article No.35.
[28] Sauer C, Jeffery DR, Land L, Yetton P. The effectiveness of software development technical reviews: A behaviorally motivated
program of research. IEEE Trans. on Software Engineering, 2000,26(1):1−14.
[29] Tantithamthavorn C, Ihara A, Matsumoto KI. Using co-change histories to improve bug localization performance. In: Proc. of the
SNPD 2013. 2013. 543−548.
[30] Jiang J, Yang Y, He J, Blanc X, Zhang L. Who should comment on this pull request? Analyzing attributes for more accurate
commenter recommendation in pull-based development. Information and Software Technology, 2017,84:48−62.
[31] Jiang J, David L, Zhang L. Who should make decision on this pull request? Analyzing time-decaying relationships and file
similarities for integrator prediction. The Journal of Systems and Software, 2019,154:196−210.
[32] Lu S, Yang D, Hu J, Zhang X. Code reviewer recommendation based on time and impact factor for pull request in Github.
Computer Systems & Applications, 2016,25(12):155−161 (in Chinese with English abstract).