Dr. Shuai Wang and Collaborators Receive ACM Distinguished Paper Award at ASE 2026

Dr. Shuai Wang of the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology (HKUST) and his collaborators have received the ACM Distinguished Paper Award at the 41st IEEE/ACM International Conference on Automated Software Engineering (ASE 2026) for their paper, "KQFuzz: Knowledge-Guided Fuzzing for Quantum Libraries via Large Language Models."

The research was conducted in collaboration with Shanghai Jiao Tong University, Nanyang Technological University, and Zhejiang University of Technology.

Quantum programming libraries underpin the development and execution of quantum algorithms. Bugs in these libraries can compromise results and waste computing resources. Testing is challenging because the libraries evolve rapidly, while both manually designed testing rules and programs generated by large language models can struggle to keep pace.

To address this challenge, the team developed KQFuzz, an automated testing framework that guides language models using knowledge extracted from the target library, including API relationships, semantics, and version changes. It then evaluates and mutates the generated programs to explore complex execution paths and expose hidden defects.

Evaluated on Qiskit, PennyLane, and Cirq, KQFuzz identified 13 previously unknown bugs, all confirmed by developers. It also achieved higher code coverage than the evaluated baselines; on Cirq, line coverage rose from 55.35% with Fuzz4All to 73.79% with KQFuzz.

Congratulations to Dr. Wang and all co-authors!

Authors (in paper order): Fuyuan Xia, Qixin Zhang, Chenhao Ying, Haojin Zhu, Shuai Wang, Yuan Luo, Pingchuan Ma, and Yuxuan Du.

Paper: https://arxiv.org/abs/2607.25647