þ Master Supervisor

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Research Areas

Static Code Analysis, Code Representation, Deep Learning, Data Mining and Analysis, Software Quality Assurance

Honors

2023 Ministry of Education - Huawei "Intelligent Foundation" Pillar Educators

Publications

[1] Qing Mi, Yi Zhan, Han Weng, Qinghang Bao, Longjie Cui, Wei Ma: A Graph-Based Code Representation Method to Improve Code Readability Classification. Empirical Software Engineering 2023 (JCR-Q1)

[2] Qing Mi, Mingjie Chen, Zhi Cai, Xibin Jia: What makes a readable code? A causal analysis method. Software Practice and Experience 2023 (JCR-Q2)

[3] Qing Mi, Yiqun Hao, Liwei Ou, Wei Ma: Towards Using Visual, Semantic and Structural Features to Improve Code Readability Classification. Journal of Systems and Software 2022 (JCR-Q2)

[4] Qing Mi, Yan Xiao, Zhi Cai, Xibin Jia: The effectiveness of data augmentation in code readability classification. Information and Software Technology 2021 (JCR-Q1)

[5] Qing Mi, Jacky Keung, Yan Xiao, Solomon Mensah, Yujin Gao: Improving code readability classification using convolutional neural networks. Information and Software Technology 2018 (JCR-Q1)

Personal Statement

Mi Qing is a lecturer in the College of Computer Science, Beijing University of Technology. She received her M.Sc. in Computer Science and Technology from the Beijing Institute of Technology in 2012 and her Ph.D. in Software Engineering from the City University of Hong Kong in 2018. Her research interests include static code analysis, code representation, deep learning, data mining and analysis, and software quality assurance. To date, she has published over 50 papers in refereed journals and conference proceedings.