Does the Role Matter? An Investigation of the Code Quality of Casual Contributors in GitHub. - Yao Lu 003; Xinjun Mao; Zude Li; Yang Zhang 026; Tao Wang 006; Gang Yin (APSEC, 2016)

Quantitative Analysis of Learning Data in a Programming Course. - Yu Bai 010; Liqian Chen; Gang Yin; Xinjun Mao; Ye Deng; Tao Wang 006; Yao Lu 003; Huaimin Wang (DASFAA Workshops, 2017)

Using Pull-Based Collaborative Development Model in Software Engineering Courses: A Case Study. - Yao Lu 003; Xinjun Mao; Gang Yin; Tao Wang 006; Yu Bai 010 (DASFAA Workshops, 2017)

Model and Practice of Crowd-Based Education. - Xinjun Mao; Yao Lu 003; Liangze Yin; Tao Wang 006; Gang Yin (APWeb/WAIM Workshops, 2018)

Continuous inspection in the classroom: improving students' programming quality with social coding methods. - Yao Lu 003; Xinjun Mao; Tao Wang 006; Gang Yin; Zude Li; Huaimin Wang (ICSE (Companion Volume), 2018)

Internal quality assurance for external contributions in GitHub: An empirical investigation. - Yao Lu 003; Xinjun Mao; Zude Li; Yang Zhang 026; Tao Wang 006; Gang Yin (J. Softw. Evol. Process., 2018)

Studying in the 'Bazaar': An Exploratory Study of Crowdsourced Learning in GitHub. - Yao Lu 003; Xinjun Mao; Tao Wang 006; Gang Yin; Zude Li; Wanyuan Wang (IEEE Access, 2019)

History-Driven Fix for Code Quality Issues. - Jiangtao Xue; Xinjun Mao; Yao Lu 003; Yue Yu 001; Shangwen Wang (IEEE Access, 2019)

An Empirical Study on the Influence of Social Interactions for the Acceptance of Answers in Stack Overflow. - Zhang Zhang 005; Xinjun Mao; Yao Lu 003; Shangwen Wang; Jinyu Lu (APSEC, 2020)

Exploiting Crowd-based Learning Method in Software Engineering Course. - Xinjun Mao; Yao Lu 003; Yi Yang 004 (ICCSE, 2020)

Gathering GitHub OSS Requirements from Q&A Community: an Empirical Study. - Hao Huang; Yao Lu 003; Xinjun Mao (ICECCS, 2020)

Haste Makes Waste: An Empirical Study of Fast Answers in Stack Overflow. - Yao Lu 003; Xinjun Mao; Minghui Zhou 001; Yang Zhang 026; Tao Wang 006; Zude Li (ICSME, 2020)

Exploring the Dependency Network of Docker Containers: Structure, Diversity, and Relationship. - Yinyuan Zhang; Yang Zhang 026; Yiwen Wu 001; Yao Lu 003; Tao Wang 006; Xinjun Mao (Internetware, 2020)

Who Should Close the Questions: Recommending Voters for Closing Questions Based on Tags. - Zhang Zhang 005; Xinjun Mao; Yao Lu 003; Jinyu Lu (SEKE, 2020)

Exploring CQA User Contributions and Their Influence on Answer Distribution. - Yi Yang 004; Xinjun Mao; Zixi Xu; Yao Lu 003 (SEKE, 2020)

Improving students' programming quality with the continuous inspection process: a social coding perspective. - Yao Lu 003; Xinjun Mao; Tao Wang 006; Gang Yin; Zude Li (Frontiers Comput. Sci., 2020)

Automatic Voter Recommendation Method for Closing Questions in Stack Overflow. - Zhang Zhang 005; Xinjun Mao; Yao Lu 003; Jinyu Lu; Yue Yu 001; Zhixing Li (Int. J. Softw. Eng. Knowl. Eng., 2020)

基于特征提取的开源社区Fork摘要自动生成方法 (Approach of Automatic Fork Summary Generation in Open Source Community Based on Feature Extraction). - Chao Zhang; Xinjun Mao; Yao Lu 003 (计算机科学, 2020)

TagNN: A Code Tag Generation Technology for Resource Retrieval from Open-Source Big Data. - Lingbin Zeng; Xin Guo; Cheng Yang 004; Yao Lu 003; Xiao Li (Wirel. Commun. Mob. Comput., 2021)

Towards a behavior tree-based robotic software architecture with adjoint observation schemes for robotic software development. - Shuo Yang 005; Xinjun Mao; Yao Lu 003; Yong Xu (Autom. Softw. Eng., 2022)

FENSE: A feature-based ensemble modeling approach to cross-project just-in-time defect prediction. - Tanghaoran Zhang; Yue Yu 001; Xinjun Mao; Yao Lu 003; Zhixing Li; Huaimin Wang (Empir. Softw. Eng., 2022)

ForkXplorer: an approach of fork summary generation. - Zhang Zhang 005; Xinjun Mao; Chao Zhang; Yao Lu 003 (Frontiers Comput. Sci., 2022)

Motivation Under Gamification: An Empirical Study of Developers' Motivations and Contributions in Stack Overflow. - Yao Lu 003; Xinjun Mao; Minghui Zhou 001; Yang Zhang 026; Zude Li; Tao Wang 006; Gang Yin; Huaimin Wang (IEEE Trans. Software Eng., 2022)

An Extensive Study of the Structure Features in Transformer-based Code Semantic Summarization. - Kang Yang 001; Xinjun Mao; Shangwen Wang; Yihao Qin; Tanghaoran Zhang; Yao Lu 003; Kamal Al-Sabahi (ICPC, 2023)

An Empirical Study of Cross-Project Pull Request Recommendation in GitHub. - Wenyu Xu; Yao Lu 003; Xunhui Zhang; Tanghaoran Zhang; Bo Lin; Xinjun Mao (APSEC, 2024)

CAREER: Context-Aware API Recognition with Data Augmentation for API Knowledge Extraction. - Zhang Zhang 005; Xinjun Mao; Shangwen Wang; Kang Yang 001; Yao Lu 003 (ICPC, 2024)

How Do Developers Adapt Code Snippets to Their Contexts? An Empirical Study of Context-Based Code Snippet Adaptations. - Tanghaoran Zhang; Yao Lu 003; Yue Yu 001; Xinjun Mao; Yang Zhang 026; Yuxin Zhao (IEEE Trans. Software Eng., 2024)

Instruct or Interact? Exploring and Eliciting LLMs' Capability in Code Snippet Adaptation Through Prompt Engineering. - Tanghaoran Zhang; Yue Yu 001; Xinjun Mao; Shangwen Wang; Kang Yang 001; Yao Lu 003; Zhang Zhang 005; Yuxin Zhao (ICSE, 2025)

Large Language Models Are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks. - Kang Yang 001; Xinjun Mao; Shangwen Wang; Yanlin Wang 001; Tanghaoran Zhang; Bo Lin; Yihao Qin; Zhang Zhang 005; Yao Lu 003; Kamal Al-Sabahi (ICPC, 2025)