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. I was supervised by Prof. Michael R. Lyu (ACM/IEEE/AAAS Fellow). 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.
【2025.04.07】Our Forge'25 paper "PerfCodeGen: Improving Performance of LLM Generated Code with Execution Feedback" has been selected ACM SIGSOFT Distinguished Paper Award!
【2025.03.06】I am glad to join the Program Committee of the Research Papers Track at ASE 2025!
【2025.01.15】Our code efficiency benchmark paper has been accepted with no revision (11.5%) by FSE 2025, the project website is here!
【2024.08.26】I am glad to join Huawei Hong Kong Research Center as a Principal Engineer! I will be developing on the automated, intelligent and reliable code review tools for the company.
【2023.10.10】Our paper on the configuration issues of PyPI ecosystem has been accepted by ICSE 2024 second cycle, the preprint is here!
【2023.09.11】Our ASE'23 paper "Generative Type Inference for Python" has been selected ACM SIGSOFT Distinguished Paper Award !
【2023.07.19】Our generative type inference paper has been accepted by ASE 2023, the preprint is here!
【2023.06.01】 Our program repair paper for Python type errors has been accepted with no revision (6.6%) by ICSE 2024 first cycle, the preprint is here !
【2022.08.04】Our empirical study on API recommendation has been accepted by TSE!
【2022.06.15】Our empirical study about prompt tuning in code intelligence has been accepted by FSE 2022!
【2021.12.23】 Our API benchmark is now open-sourced at Zenodo, and our empirical study on API recommendation is available at Arxiv!
【2021.12.03】 Our type inference paper has been accepted by ICSE 2022 and nominated for ACM SIGSOFT Distinguished Paper Award !
Selected Publications
COFFE: A Code Efficiency Benchmark for Code Generation.
Yun Peng, Jun Wan, Yichen Li, Xiaoxue Ren
The ACM International Conference on the Foundations of Software Engineering, Trondheim, Norway, Jun 23 - 27, 2025
ACM SIGSOFT Distinguished Paper Award
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
46th International Conference on Software Engineering, Lisbon, Portugal, Apr 14-20, 2024
Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors.
Yun Peng, Shuzheng Gao, Cuiyun Gao, Yintong Huo, Michael R. Lyu
46th International Conference on Software Engineering, Lisbon, Portugal, Apr 14-20, 2024
Generative Type Inference for Python.
Yun Peng, Chaozheng Wang, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu
38th IEEE/ACM International Conference on Automated Software Engineering, Kirchberg, Luxembourg, Sep 11-15, 2023
ACM SIGSOFT Distinguished Paper Award
Revisiting, Benchmarking and Exploring API Recommendation: How Far Are We?
Yun Peng, Shuqing Li, Wenwei Gu, Yichen Li, Wenxuan Wang, Cuiyun Gao, Michael Lyu
IEEE Transactions on Software Engineering
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
44th International Conference on Software Engineering, Pittsburgh, PA, USA, May 21-29, 2022
ACM SIGSOFT Distinguished Paper Award Nomination
An Empirical Study for Common Language Features Used in Python Projects.
Yun Peng, Yu Zhang, Mingzhe Hu
28th IEEE International Conference on Software Analysis, Evolution and Reengineering, Honolulu, HI, USA, March 9-12, 2021
Recent Research
ASE 2023
Generative Type Inference for Python ASE 2023 Paper Information Paper Name: Generative Type Inference for Python Conference: 38th IEEE/ACM International…
TSE 2022
Revisiting, Benchmarking and Exploring API Recommendation: How Far Are We? TSE 2022 Paper Information Paper Name: Revisiting, Benchmarking and Exploring…
ICSE22
Static Inference Meets Deep Learning: A Hybrid Type Inference Approach for Python ICSE 2022 Paper Information Paper Name: Static Inference…
SANER2021
An Empirical Study for Common Language Features Used in Python Projects SANER 2021 Paper Information Paper Name: An Empirical Study for…