CS Special Seminar: Sidong Feng "Rethinking Software Testing: How AI Helps Us Test Less and Test Smarter"
When
Where
Event language(s)
Rethinking Software Testing: How AI Helps Us Test Less and Test Smarter
Sidong Feng
Monash University
Google Scholar
Abstract: TBA
Bio: Sidong Feng is a final-year PhD candidate at Monash University, supervised by Chunyang Chen, Aldeida Aleti, Yuan-Fang Li, and Bohan Zhuang. He holds a Bachelor’s degree with Honours in Software Engineering from the Australian National University. His research lies at the intersection of software engineering (SE) and human-computer interaction (HCI), with a multidisciplinary focus on intelligent software development and testing. His work has led to several influential publications in top-tier SE venues including ICSE, FSE, ASE, and ISSTA, as well as leading HCI conferences such as CHI, UIST, CSCW, and IUI. His contributions have been recognized with the ACM SIGSOFT Distinguished Paper Award at ICSE 2023 and a Highlight Paper Award at IUI 2021. Sidong's research has directly impacted testing workflows in large-scale industrial settings by enhancing over 10k tests, identifying more than 150 real-world bugs, and reducing testing time by 88% at companies like Tencent and TikTok.
Department of Computer Science
We are an internationally-oriented community and home to world-class research in modern computer science.