Research Scientist · Software Engineering

Weifeng Sun

I study intelligent software engineering, with a focus on AI for software engineering and software engineering for AI systems.

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I am currently a research scientist at Singapore Management University, advised by Prof. David Lo.

Prior to that, I received my Ph.D. degree from Chongqing University, China, under the supervision of Dr. Meng Yan.

My research interest is intelligent software engineering. My work involves both Artificial Intelligence for Software Engineering (AI4SE) and Software Engineering for Artificial Intelligence (SE4AI). In terms of AI4SE, I study how large language models and learning-based techniques can support software development tasks, including code generation, assertion generation, test generation, test selection, traceability recovery, bug report understanding, and software evolution analysis. In terms of SE4AI, I focus on improving the reliability, security, and maintainability of AI-enabled software systems, especially code LLMs and deep code models, through testing, adversarial analysis, jailbreak attack assessment, and generation-quality enhancement.

Selected Publications

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14 selected · † first author 9 · ✰ co-first author 3 · * corresponding author 2

  1. TSE
    Cost-Effective Adversarial Attacks Against Code LLM with Model Attention †
    Weifeng Sun, Naiqi Huang, Meng Yan, Li Huang, Zhongxin Liu, Xiao Liu, and David Lo
    IEEE Transactions on Software Engineering (TSE, CCF-A), 2026
  2. TOSEM
    On-the-Fly Generation-Quality Enhancement of Deep Code Models via Model Collaboration †
    Weifeng Sun, Naiqi Huang, Meng Yan, Zhongxin Liu, Hongyan Li, Yan Lei, and David Lo
    ACM Transactions on Software Engineering and Methodology (TOSEM, CCF-A), 2026
  3. EMSE
    Exploring and improving knowledge distillation for pre-trained code models †
    Weifeng Sun, Ruifeng Wu, Hongyan Li, Ying Fu, Min Yu, and Meng Yan
    Empirical Software Engineering (EMSE, CCF-B), 2026
  4. ACL Findings
    MultiCodeAttack: Iterative Jailbreak Attacking on LLMs with Multi-Code Prompt Injection †
    Weifeng Sun, Meng Yan, Zhou Yang, Yuchen Chen, Song Sun, and David Lo
    In Findings of the Association for Computational Linguistics: ACL 2026 (ACL, CCF-A), 2026
  5. TSE
    Retrieval-Augmented Fine-Tuning for Improving Retrieve-and-Edit Based Assertion Generation ✰
    Hongyan Li, Weifeng Sun, Meng Yan, Ling Xu, Qiang Li, Xiaohong Zhang, and Hongyu Zhang
    IEEE Transactions on Software Engineering (TSE, CCF-A), 2025
  6. ASEJ
    TAB: Template-Aware Bug Report Title Generation via Two-Phase Fine-tuned Models *
    Xiao Liu, Yinkang Xu, Weifeng Sun, Naiqi Huang, Song Sun, Qiang Li, Dan Yang, and Meng Yan
    Automated Software Engineering (ASEJ, CCF-B), 2025
  7. TSE
    Method-Level Test-to-Code Traceability Link Construction by Semantic Correlation Learning †
    Weifeng Sun, Zhenting Guo, Meng Yan, Zhongxin Liu, Yan Lei, and Hongyu Zhang
    IEEE Transactions on Software Engineering (TSE, CCF-A), 2024
  8. TOSEM
    Exploring Automated Assertion Generation via Large Language Models ✰
    Quanjun Zhang, Weifeng Sun, Chunrong Fang, Bowen Yu, Hongyan Li, Meng Yan, Jianyi Zhou, and Zhenyu Chen
    ACM Transactions on Software Engineering and Methodology (TOSEM, CCF-A), 2024
  9. TOSEM
    Neuron Semantic-Guided Test Generation for Deep Neural Networks Fuzzing ✰
    Li Huang, Weifeng Sun, Meng Yan, Zhongxin Liu, Yan Lei, and David Lo
    ACM Transactions on Software Engineering and Methodology (TOSEM, CCF-A), 2024
  10. TSE
    Robust Test Selection for Deep Neural Networks †
    Weifeng Sun, Meng Yan, Zhongxin Liu, and David Lo
    IEEE Transactions on Software Engineering (TSE, CCF-A), 2023
  11. TOSEM
    Revisiting the Identification of the Co-Evolution of Production and Test Code †
    Weifeng Sun, Meng Yan, Zhongxin Liu, Xin Xia, Yan Lei, and David Lo
    ACM Transactions on Software Engineering and Methodology (TOSEM, CCF-A), 2023
    PDF
  12. ASE
    Revisiting and Improving Retrieval-Augmented Deep Assertion Generation †
    Weifeng Sun, Hongyan Li, Meng Yan, Yan Lei, and Hongyu Zhang
    In The 38th IEEE/ACM International Conference on Automated Software Engineering (ASE, CCF-A), Full paper, 2023
    PDF
  13. SCP
    A nearest-neighbor divide-and-conquer approach for adaptive random testing *
    Rubing Huang, Weifeng Sun, Haibo Chen, Chenhui Cui, and Ning Yang
    Science of Computer Programming (SCP, CCF-B, Corresponding Author), 2022
    PDF
  14. TSE
    A survey on adaptive random testing †
    Rubing Huang, Weifeng Sun, Yinyin Xu, Haibo Chen, Dave Towey, and Xin Xia
    IEEE Transactions on Software Engineering (TSE, CCF-A), 2019
    PDF