Novices Comprehending Functional vs. Imperative Programs: An Eye-Tracking Study. TOSEM
Zihan Fang, Weizhe Jiao, Robert Tairas, Yu Huang
[PDF]

ScanCoder: Leveraging Human Attention Patterns to Enhance LLMs for Code. FSE 2026
Yueke Zhang, Yifan Zhang, Zihan Fang, Greg Trafton, Daniel Levin, Kevin Leach, Yu Huang
[PDF]

Locating Software Vulnerabilities With Static Analyzers: How Far Are We? EASE 2026
Yueke Zhang, Zihan Fang, Kevin Leach, Yu Huang
[PDF]

Investigating the Feasibility of Conducting Webcam-Based Eye-Tracking Studies in Code Comprehension. TSE
Zihan Fang, Robert Wallace, Zachary Karas, Toby Li, Collin McMillan, Yu Huang
[PDF]

Contribution Patterns in Open Source Software for Social Good: Dynamics, Individuals, and Impact. CSCW’2026
Zihan Fang, Yueke Zhang, Thomas Zimmermann, Denae Ford, Yu Huang
[PDF]

CodeACT-R: A Cognitive Simulation Framework for Code Reading. ASE 2025-NIER
Yueke Zhang, Zihan Fang, Greg Trafton, Daniel Levin, Kevin Leach, Yu Huang
[PDF]

A Comparative Study on ChatGPT and Checklist as Support Tools for Unit Testing Education. FSE 2025-SEET
Zihan Fang, Jiliang Li, Anda Liang, Gina R. Bai, Yu Huang
[PDF]

“Math Is a Pain!”: Understanding Challenges and Needs of the Machine Learning Community on Stack Overflow. CSCW 2024
Zihan Fang, Yu Huang
[PDF]

A Four-Year Study of Student Contributions to OSS vs. OSS4SG with a Lightweight Intervention. FSE 2023
Zihan Fang, Madeline Endres, Thomas Zimmermann, Denae Ford, Westley Weimer, Kevin Leach, Yu Huang
🏆 ACM SIGSOFT Distinguished Paper Award [PDF]