Xinyue Liu (刘心悦)
I’m currently an assistant professor (弘深青年教师) at Chongqing University (重庆大学), School of Big Data & Software engineering. Before I joined Chongqing University, I was advised by Lukasz Ziarek at University at Buffalo, USA. My research interest focus on software engineering and programming language. More specifically, I’m working on automated testing and detection of web applications. Besides, I am also interested in the validation and application of a new web language — WebAssembly — the future of the web.
You can contact me through the email: aaronxyliu@gmail.com.
A printable CV of mine can be found here.
If you are a new Ph.D. student who wants to explore the path on software engineering and programming language theory, you may be interested in reading my blog series Randomized Algorithm and Easy Foundations for Programming Languages.
Education
- 2016 Fall - 2020 Summer: Nanjing University (NJU 南京大学), Bachelor
- 2021 Spring - 2025 Summer: University at Buffalo (UB), Ph.D.
Publications
X. Liu, L. Ziarek, “PTV: Better Version Detection on JavaScript Web Library Based on Unique Subtree Mining,” The ACM International Conference on the Foundations of Software Engineering (FSE 2025). [pdf1] [review1] [rebuttal1] [pdf2] [review2] [rebuttal2]
X. Liu, Z. Song, W. Fang, W. Yang, W. Wang, “WEFix: Intelligent Automatic Generation of Explicit Waits for Efficient Web End-to-End Flaky Tests,” The Web Conference 2024 (WWW 2024). (Acceptance: 20.2%, 405/2008) [pdf] [review]
X. Liu, L. Ziarek, “PTdetector: An Automated JavaScript Front-end Library Detector,” 38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023). (Acceptance: 21%, 103/629) [pdf] [review]
Y. Yan, Y. Zheng, X. Liu, N. Medvidovic, W. Wang, “AdHere: Automated Detection and Repair of Intrusive Ads,” 45th IEEE/ACM International Conference on Software Engineering (ICSE 2023). (Acceptance: 26%, 209/796) [pdf]
A. Romano, X. Liu, Y. Kwon, W. Wang, “An Empirical Study of Bugs in WebAssembly Compilers,” 36th IEEE/ACM International Conference on Automated Software Engineering (ASE 2021). (Acceptance: 19.2%, 82/427) [pdf]
X. Liu, Yanhui Li , “Is Bigger Data Better for Defect Prediction: Examining the Impact of Data Size on Supervised and Unsupervised Defect Prediction,” 12 pages, Sep. 2019, WISA 2019 [pdf]