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Yun Peng
Principal Engineer at Huawei HK Research Center
  • Chinese Name
    彭昀
  • Major
    Computer Science
  • City
    Hong Kong
  • Age
    24
  • Email
    normal@yunpeng.work
Research Interest
Software Engineering
Artificial Intelligence

Yun Peng

<code> Ph.D. in Computer Science and Engineering </code>
Photo

About Me

I am currently a principal engineer at Huawei Hong Kong Research Center. I am also an honorary research associate at The Chinese University of Hong Kong.
I am currently looking for talented PhD students for internship at Huawei HKRC. Please drop me an email with your CV if you are interested.

I received my PhD degree at the Computer Science and Engineering Department of The Chinese University of Hong Kong (CUHK) in 2024. My PhD thesis is on the run-time reliability engineering of Python software, in which I propose intelligent code analysis methods to avoid, detect and fix the run-time errors of Python software.

I received my bachelor's degree (with honors) in computer science and technology in Special Class for the Gifted Young (SCGY) from the University of Science and Technology of China (USTC) in 2020.

Selected Publications

  • ICSE
    Less is More? An Empirical Study on Configuration Issues in Python PyPI Ecosystem.
    Yun Peng, Ruida Hu, Ruoke Wang, Cuiyun Gao, Shuqing Li, Michael R. Lyu
  • ICSE
    Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors.
    Yun Peng, Shuzheng Gao, Cuiyun Gao, Yintong Huo, Michael R. Lyu
  • arxiv
    Generative Type Inference for Python.
    Yun Peng, Chaozheng Wang, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu
    ACM SIGSOFT Distinguished Paper Award
  • arxiv
    Revisiting, Benchmarking and Exploring API Recommendation: How Far Are We?
    Yun Peng, Shuqing Li, Wenwei Gu, Yichen Li, Wenxuan Wang, Cuiyun Gao, Michael Lyu
  • ICSE
    Static Inference Meets Deep Learning: A Hybrid Type Inference Approach for Python.
    Yun Peng, Cuiyun Gao, Zongjie Li, Bowei Gao, David Lo, Qirun Zhang, Michael Lyu
    ACM SIGSOFT Distinguished Paper Award Nomination
  • saner
    An Empirical Study for Common Language Features Used in Python Projects.
    Yun Peng, Yu Zhang, Mingzhe Hu
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