| Local-based active classification of test report to assist crowdsourced testing J Wang, S Wang, Q Cui, Q Wang Proceedings of the 31st IEEE/ACM International Conference on Automated …, 2016 | 70 | 2016 |
| Towards effectively test report classification to assist crowdsourced testing J Wang, Q Cui, Q Wang, S Wang Proceedings of the 10th ACM/IEEE International Symposium on Empirical …, 2016 | 64 | 2016 |
| Images don’t lie: Duplicate crowdtesting reports detection with screenshot information J Wang, M Li, S Wang, T Menzies, Q Wang Information and Software Technology 110, 139-155, 2019 | 48 | 2019 |
| Is there a" golden" feature set for static warning identification? an experimental evaluation J Wang, S Wang, Q Wang Proceedings of the 12th ACM/IEEE international symposium on empirical …, 2018 | 36 | 2018 |
| Owl eyes: Spotting ui display issues via visual understanding Z Liu, C Chen, J Wang, Y Huang, J Hu, Q Wang Proceedings of the 35th IEEE/ACM International Conference on Automated …, 2020 | 35 | 2020 |
| Domain adaptation for test report classification in crowdsourced testing J Wang, Q Cui, S Wang, Q Wang 2017 IEEE/ACM 39th International Conference on Software Engineering …, 2017 | 33 | 2017 |
| A simulation approach for impact analysis of requirement volatility considering dependency change J Wang, J Li, Q Wang, H Zhang, H Wang Requirements Engineering: Foundation for Software Quality: 18th …, 2012 | 30 | 2012 |
| Multi-Objective Crowd Worker Selection in Crowdsourced Testing. Q Cui, S Wang, J Wang, Y Hu, Q Wang, M Li SEKE 17, 218-223, 2017 | 27 | 2017 |
| Who should be selected to perform a task in crowdsourced testing? Q Cui, J Wang, G Yang, M Xie, Q Wang, M Li 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC …, 2017 | 23 | 2017 |
| Analyzing and predicting software integration bugs using network analysis on requirements dependency network J Wang, Q Wang Requirements Engineering 21, 161-184, 2016 | 23 | 2016 |
| Characterizing crowds to better optimize worker recommendation in crowdsourced testing J Wang, S Wang, J Chen, T Menzies, Q Cui, M Xie, Q Wang IEEE Transactions on Software Engineering 47 (6), 1259-1276, 2019 | 21 | 2019 |
| Can requirements dependency network be used as early indicator of software integration bugs? J Wang, J Li, Q Wang, D Yang, H Zhang, M Li 2013 21st IEEE International Requirements Engineering Conference (RE), 185-194, 2013 | 17 | 2013 |
| iSENSE: Completion-aware crowdtesting management J Wang, Y Yang, R Krishna, T Menzies, Q Wang 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE …, 2019 | 16 | 2019 |
| Characterizing and Predicting Good First Issues Y Huang, J Wang, S Wang, Z Liu, D Wang, Q Wang Proceedings of the 15th ACM/IEEE International Symposium on Empirical …, 2021 | 15 | 2021 |
| Automatic unit test generation for machine learning libraries: How far are we? S Wang, N Shrestha, AK Subburaman, J Wang, M Wei, N Nagappan 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE …, 2021 | 15 | 2021 |
| Context-aware in-process crowdworker recommendation J Wang, Y Yang, S Wang, Y Hu, D Wang, Q Wang Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 15 | 2020 |
| Understanding static code warnings: An incremental AI approach X Yang, Z Yu, J Wang, T Menzies Expert Systems with Applications 167, 114134, 2021 | 13 | 2021 |
| Enhancing unsupervised requirements traceability with sequential semantics L Chen, D Wang, J Wang, Q Wang 2019 26th Asia-Pacific Software Engineering Conference (APSEC), 23-30, 2019 | 12 | 2019 |
| Context-aware personalized crowdtesting task recommendation J Wang, Y Yang, S Wang, C Chen, D Wang, Q Wang IEEE Transactions on Software Engineering 48 (8), 3131-3144, 2021 | 10 | 2021 |
| CLEAR: contrastive learning for API recommendation M Wei, NS Harzevili, Y Huang, J Wang, S Wang Proceedings of the 44th International Conference on Software Engineering …, 2022 | 9 | 2022 |
Song WangAssistant Professor at York University, CanadaVerified email at eecs.yorku.ca
