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Wanwangying Ma
Wanwangying Ma
Verified email at smail.nju.edu.cn
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Cited by
Year
How do developers fix cross-project correlated bugs? a case study on the github scientific python ecosystem
W Ma, L Chen, X Zhang, Y Zhou, B Xu
2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE …, 2017
872017
Empirical analysis of network measures for effort-aware fault-proneness prediction
W Ma, L Chen, Y Yang, Y Zhou, B Xu
Information and Software Technology 69, 50-70, 2016
642016
Understanding metric-based detectable smells in Python software: A comparative study
Z Chen, L Chen, W Ma, X Zhou, Y Zhou, B Xu
Information and Software Technology 94, 14-29, 2018
402018
Detecting code smells in Python programs
Z Chen, L Chen, W Ma, B Xu
2016 international conference on Software Analysis, Testing and Evolution …, 2016
402016
Do we have a chance to fix bugs when refactoring code smells?
W Ma, L Chen, Y Zhou, B Xu
2016 international conference on software analysis, testing and evolution …, 2016
302016
An empirical study on the impact of Python dynamic features on change-proneness.
B Wang, L Chen, W Ma, Z Chen, B Xu
SEKE, 134-139, 2015
282015
An empirical study on the characteristics of Python fine-grained source code change types
W Lin, Z Chen, W Ma, L Chen, L Xu, B Xu
2016 IEEE international conference on software maintenance and evolution …, 2016
242016
An empirical study on dynamic typing related practices in python systems
Z Chen, Y Li, B Chen, W Ma, L Chen, B Xu
Proceedings of the 28th International Conference on Program Comprehension, 83-93, 2020
202020
A study on the changes of dynamic feature code when fixing bugs: towards the benefits and costs of Python dynamic features
Z Chen, W Ma, W Lin, L Chen, Y Li, B Xu
Science China Information Sciences 61, 1-18, 2018
202018
What are the factors impacting build breakage?
Y Luo, Y Zhao, W Ma, L Chen
2017 14th Web Information Systems and Applications Conference (WISA), 139-142, 2017
192017
Empirical analysis of network measures for predicting high severity software faults
L Chen, W Ma, Y Zhou, L Xu, Z Wang, Z Chen, B Xu
Science China Information Sciences 59, 1-18, 2016
192016
What are the dominant projects in the github python ecosystem?
W Ma, L Chen, Y Zhou, B Xu
2016 Third International Conference on Trustworthy Systems and their …, 2016
192016
Towards better dependency management: A first look at dependency smells in python projects
Y Cao, L Chen, W Ma, Y Li, Y Zhou, L Wang
IEEE Transactions on Software Engineering, 2022
182022
Impact analysis of cross-project bugs on software ecosystems
W Ma, L Chen, X Zhang, Y Feng, Z Xu, Z Chen, Y Zhou, B Xu
Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020
162020
CBUA: A probabilistic, predictive, and practical approach for evaluating test suite effectiveness
P Zhang, Y Li, W Ma, Y Yang, L Chen, H Lu, Y Zhou, B Xu
IEEE Transactions on Software Engineering 48 (3), 1067-1096, 2020
122020
How do developers fix cross-project correlated bugs? a case study on the GitHub scientific Python ecosystem. In 2017 IEEE/ACM 39th International Conference on Software …
W Ma, L Chen, X Zhang, Y Zhou, B Xu
IEEE, 381ś392, 2017
112017
Are anti-patterns coupled? an empirical study
W Ma, L Chen, Y Zhou, B Xu, X Zhou
2015 IEEE International conference on software quality, reliability and …, 2015
112015
Collaboration in software ecosystems: A study of work groups in open environment
Z Chen, W Ma, L Chen, W Song
Information and Software Technology 145, 106849, 2022
92022
An empirical study on downstream workarounds for cross-project bugs
H Ding, W Ma, L Chen, Y Zhou, B Xu
2017 24th Asia-Pacific Software Engineering Conference (APSEC), 318-327, 2017
92017
How C++ templates are used for generic programming: an empirical study on 50 open source systems
L Chen, D Wu, W Ma, Y Zhou, B Xu, H Leung
ACM Transactions on Software Engineering and Methodology (TOSEM) 29 (1), 1-49, 2020
82020
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