Yepang Liu (CV)
Tenure-Track Assistant Professor
Department of Computer Science and Engineering
Southern University of Science and Technology
Office: Room 609, CoE Building (South), SUSTech
Email: liuyp1 AT sustech DOT edu DOT cn
I am an assistant professor with the CSE Department of SUSTech. I lead the Software Quality Lab. I am also the co-ordinator of the Trustworthy Software Research Center of the Research Insititute of Trustworthy Autonomous Systems. My research interests mainly include software testing and analysis, empirical software engineering, cyber-physical systems, mobile computing, and cybersecurity. I obtained my B.Sc. degree in Computer Science with honor from Nanjing University in 2010, and my Ph.D. degree in Computer Science and Engineering from HKUST in 2015. Prior to joining SUSTech, I worked at the CASTLE Lab and Cybersecurity Lab of HKUST as a postdoc, under the supervision of Prof. Shing-Chi Cheung and Prof. Charles Zhang.
[ISSTA 2023, CCF-A] Huaxun Huang, Chi Xu, Ming Wen, Yepang Liu, and Shing-Chi Cheung. ConfFix: Repairing Configuration Compatibility Issues in Android Apps. In the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2023, to appear.
[ICST 2023, CCF-C] Jiayuan Liang, Sinan Wang, Xiangbo Deng, and Yepang Liu. RIDA: Cross-App Record and Replay for Android. In the 16th IEEE International Conference on Software Testing, Verification and Validation, 2023, to appear. [preprint]
[ICSE 2023, CCF-A] Jiwei Yan, Miaomiao Wang, Yepang Liu, Jun Yan, and Long Zhang. Locating Framework-specific Crashing Faults with Compact and Explainable Candidate Set. In the 45th International Conference on Software Engineering, 2023, to appear. [pdf]
[ICSE 2023, CCF-A] Hao Guan, Ying Xiao, Jiaying Li, Yepang Liu, and Guangdong Bai. A Comprehensive Study of Real-World Bugs in Machine Learning Model Optimization. In the 45th International Conference on Software Engineering, 2023, to appear.
[SCIS 2022, CCF-A] Yingfei Xiong, Yongqiang Tian, Yepang Liu, and Shing-Chi Cheung. Towards Actionable Testing of Deep Learning Models. In Science China Information Sciences, 2022, to appear. [pdf]
[ISSRE 2022, CCF-B] Yue Liu, Chakkrit Tantithamthavorn, Li Li, and Yepang Liu. Explainable AI for Android Malware Detection: Towards Understanding Why the Models Perform So Well? In the 33rd International Symposium on Software Engineering Reliability, 2022, to appear.
[MICRO 2022, CCF-A] Xueliang Li, Zhuobin Shi, Junyang Chen, and Yepang Liu. Realizing Emotional Interactions to Learn User Experience and Guide Energy Optimization for Mobile Architectures. In the 55th IEEE/ACM International Symposium on Microarchitecture, 2022, to appear.
[CSUR 2022, JCR-Q1] Yue Liu, Chakkrit Tantithamthavorn, Li Li, and Yepang Liu. Deep Learning for Android Malware Defenses: a Systematic Literature Review. In ACM Computing Surveys, 2022, to appear.
[TSE 2022, CCF-A] Ying Wang, Yibo Wang, Sinan Wang, Yepang Liu, Chang Xu, Shing-Chi Cheung, Hai Yu, and Zhiliang Zhu. Runtime Permission Issues in Android Apps: Taxonomy, Practices, and Ways Forward. In IEEE Transactions on Software Engineering, to appear.
[ICSE 2022, CCF-A] Sinan Wang, Yibo Wang, Xian Zhan, Ying Wang, Yepang Liu, Xiapu Luo, and Shing-Chi Cheung. Aper: Evolution-Aware Runtime Permission Misuse Detection for Android Apps. In the 44th International Conference on Software Engineering, pp. 125-137, May 2022, to appear. [pdf][tool]