Image Yepang Liu (刘烨庞, CV)

Associate Professor (博导, 研究员)
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
Tel: +86-0755-88015159

I am a tenured associate professor with the CSE Department of SUSTech. I lead the Software Quality Lab. I am also the director 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, software security, and trustworthy AI. Our research is supported by the National Natural Science Foundation of China, National Key Research and Development Program of China, Basic and Applied Basic Research Foundation of Guangdong, Science, Technology and Innovation Commission of Shenzhen, and leading IT companies in China. 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.

Call for papers: Please consider submitting your high-quality work to ICSE 2025, FSE 2025, SANER 2025, ASE 2024, JCST, where I serve as a PC member or an editor.

We are hiring research assistant professors, postdocs, and research assistants (job post). We are also looking for PhD students with strong programming skills and good English ability. Please send me an email with your CV if you are interested and have relevant background. For undergraduate students who are interested in joining our group, please send me a copy of your transcript.

Latest News (more)

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Teaching (more)

Selected Recent Publications (full list, Google Scholar)

  1. [ASE 2024, CORE-A*/CCF-A] Yujia Fan, Sinan Wang, Zebang Fei, Yao Qin, Huaxuan Li, and Yepang Liu. Can Cooperative Multi-Agent Reinforcement Learning Boost Automatic Web Testing? An Exploratory Study. In the 39th IEEE/ACM International Conference on Automated Software Engineering, October 2024, Sacremento, California, United States, pp. 14-26. [pdf]

  2. [ASE 2024 Demonstration] Yige Chen, Sinan Wang, Yida Tao, and Yepang Liu. Model-based GUI Testing for HarmonyOS Apps. In the Demonstration Track of the 39th IEEE/ACM International Conference on Automated Software Engineering, October 2024, Sacramento, California, United States, pp. 2411-2414. [PDF][Code][Demo (English)][Demo (Chinese)]

  3. [ISSTA 2024, CORE-A*/CCF-A] Hao Guan, Guangdong Bai, and Yepang Liu. Large Language Models Can Connect the Dots: Exploring Model Optimization Bugs with Domain Knowledge-aware Prompts. In the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis, September 2024, Vienna, Austria, pp. 1579-1591. [acceptance rate: 20.6%][pdf]

  4. [ICSME 2024, CORE-A/CCF-B] Siyi Wang, Sinan Wang, Yujia Fan, Xiaolei Li, and Yepang Liu. Leveraging Large Vision-Language Model for Better Automatic Web GUI Testing. In the 40th IEEE International Conference on Software Maintenance and Evolution, October 2024, Flagstaff, AZ, USA. [acceptance rate: 26%][pdf]

  5. [ICSME 2024, CORE-A/CCF-B] Junfeng Chen, Kevin Li, Yifei Chen, Lili Wei, and Yepang Liu. Demystifying Device-specific Compatibility Issues in Android Apps. In the 40th IEEE International Conference on Software Maintenance and Evolution, October 2024, Flagstaff, AZ, USA, to appear. [pdf][acceptance rate: 26%]

  6. [FSE 2024, CORE-A*/CCF-A] Ying Xiao, Jie M. Zhang, Yepang Liu, Mohammad Reza Mousavi, Sicen Liu, and Dingyuan Xue. MirrorFair: Fixing Fairness Bugs in Machine Learning Software via Counterfactual Predictions. In the ACM International Conference on the Foundations of Software Engineering, July 2024, Porto de Galinhas, Brazil, to appear. [pdf]

  7. [FSE 2024, CORE-A*/CCF-A] Shuqing Li, Cuiyun Gao, Jianping Zhang, Yujia Zhang, Yepang Liu, Jiazhen Gu, Yun Peng, and Michael R. Lyu. Less Cybersickness, Please: Demystifying and Detecting Stereoscopic Visual Inconsistencies in Virtual Reality Applications. In the ACM International Conference on the Foundations of Software Engineering, July 2024, Porto de Galinhas, Brazil, to appear. [pdf]

  8. [ICSE 2024, CORE-A*/CCF-A] Dinghua Wang, Shuqing Li, Guanping Xiao, Yepang Liu, Yulei Sui, Pinjia He, and Michael R. Lyu. An Exploratory Investigation of Log Anomalies in Unmanned Aerial Vehicles. In the 46th International Conference on Software Engineering, April 2024, Lisbon, Portugal. [pdf]

  9. [TSE 2023, CCF-A] Wuqi Zhang, Lili Wei, Shing-Chi Cheung, Yepang Liu, Shuqing Li, Lu Liu, and Michael R. Lyu. Combatting Front-Running in Smart Contracts: Attack Mining, Benchmark Construction and Vulnerability Detector Evaluation. In IEEE Transactions on Software Engineering, to appear. [preprint]

  10. [OOPSLA 2023, CORE-A/CCF-A] Shangwen Wang, Bo Lin, Zhensu Sun, Ming Wen, Yepang Liu, Yan Lei, and Xiaoguang Mao. Two Birds with One Stone: Boosting Code Generation and Code Search via Generative Adversarial Network. In the 2023 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications, October 2023, Cascais, Portugal, 30 pages. [pdf]

  11. [ISSTA 2023, CCF-A] Linlin Li, Ruifeng Wang, Xian Zhan, Ying Wang, Cuiyun Gao, Sinan Wang, and Yepang Liu. What You See Is What You Get? It Is Not the Case! Detecting Misleading Icons for Mobile Applications. In the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2023, July 2023, pp. 538-550. [pdf]

  12. [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.

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