About
I am actively seeking faculty jobs worldwide!
I will be attending ICSE'24 in Lisbon. Looking forward to meeting you there and enjoy a coffee chat ☕️.
I am a final-year CSE Ph.D. student at the Chinese University of Hong Kong, advised by Prof. Michael R. Lyu. I received my Bachelor's degree from the University of Electronic Science and Technology of China in 2020. My research focuses on intelligent software engineering, which applies AI (mostly NLP) technologies to facilitate automated software development, testing, and operations.
The goal of my research is to ensure software reliability by enabling automated software reliability engineering. Generally, I am interested in following research topics:
I will be attending ICSE'24 in Lisbon. Looking forward to meeting you there and enjoy a coffee chat ☕️.
I am a final-year CSE Ph.D. student at the Chinese University of Hong Kong, advised by Prof. Michael R. Lyu. I received my Bachelor's degree from the University of Electronic Science and Technology of China in 2020. My research focuses on intelligent software engineering, which applies AI (mostly NLP) technologies to facilitate automated software development, testing, and operations.
The goal of my research is to ensure software reliability by enabling automated software reliability engineering. Generally, I am interested in following research topics:
- Code production: Provide automated code suggestions by boosting program analysis with NLP techniques (e.g., large language models).
- Code repair: Develop automatic code-repairing approaches.
- Software operation: Identify, localize and analyze faults/anomalies via system logs.
NEWS
- [2024/04] I have been invited to serve on the Program Committee for ISSRE 2024 and ICSE 2025. Looking forward to great submissions!
- [2024/04] The first & most large-scale empirical study about "LLMs for logging" is available online! Check the paper and see how LLMs can be a smart logging assistant 🚀. Thank you all co-authors to make this paper happen!
- [2024/03] Two papers are accepted by 2024 ISSTA Research Track! (1) Congrats to Zhihan! Check our LogPub (LogHub 2.0) for a large-scale log parsing benchmark; and (2) Special congratulation to Shiwen, who conducted her work in our undergrad summer visiting program. Feel free to reach out to me if you also want to do cool summer research!
- [2024/01] Two papers about “LLM for log analysis” are accepted by 2024 FSE Research Track (56/483)! Congratulations to Yichen and Zhihan!
- [2024/01] One paper about "LLM for programming" is accepted by ICSE-LLM4Code.
- [2023/10] Our paper "DivLog: Log Parsing with Prompt Enhanced In-Context Learning" has been accepted by 2024 ICSE Technical Track.
- [2023/07] Our paper "AutoLog: A Log Sequence Synthesis Framework for Anomaly Detection" has been accepted by 2023 ASE Research Track.
Publications
(# Equal contribution, * Corresponding author)
- (Preprint) Exploring the Effectiveness of LLMs in Automated Logging Generation: An Empirical Study [PDF] [Dataset: LogBench]
Yichen Li#, Yintong Huo#, Zhihan Jiang, Renyi Zhong, Pinjia He, Yuxin Su, Lionel C. Briand, and Michael R. Lyu. - Face It Yourselves: An LLM-based Two-Stage Strategy to Localize Configuration Errors via Logs [PDF]
Shiwen Shan, Yintong Huo, Yuxin Su, Yichen Li, Dan Li, and Zibin Zheng. To appear in the ACM International Symposium on Software Testing and Analysis (ISSTA), 2024 - A Large-scale Evaluation for Log Parsing Techniques: How Far are We? [PDF] [Dataset: LogPub]
Zhihan Jiang, Jinyang Liu, Junjie Huang, Yichen Li, Yintong Huo, Jiazhen Gu, Zhuangbin Chen, Jieming Zhu, and Michael R. Lyu. To appear in the ACM International Symposium on Software Testing and Analysis (ISSTA), 2024 - Go Static: Contextualized Logging Statement Generation [PDF]
Yichen Li, Yintong Huo*, Renyi Zhong, Zhihan Jiang, Jinyang Liu, Junjie Huang, Jiazhen Gu, Pinjie He, and Michael R. Lyu. To appear in the ACM International Conference on the Foundations of Software Engineering (FSE), 2024 - LILAC: Log Parsing using LLMs with Adaptive Parsing Cache [PDF]
Zhihan Jiang, Jinyang Liu, Zhuangbin Chen, Yichen Li, Junjie Huang, Yintong Huo, Pinjie He, Jiazhen Gu, and Michael R. Lyu. To appear in the ACM International Conference on the Foundations of Software Engineering (FSE), 2024 - Enhancing LLM-based Coding Tools Through Native Integration of IDE-Derived Static Context [PDF]
Yichen Li, Yun Peng, Yintong Huo*, and Michael R. Lyu. To appear in the IEEE/ACM International Conference on Software Engineering Workshop on Large Language Model for Code (ICSE-LLM4Code), 2024 - DivLog: Log Parsing with Prompt Enhanced In-Context Learning [PDF]
Junjielong Xu, Ruichun Yang, Yintong Huo, Chengyu Zhang, Pinjia He.Proceedings of 44th International Conference on Software Engineering (ICSE), 2024 - AutoLog: A Log Sequence Synthesis Framework for Anomaly Detection [PDF]
Yintong Huo#, Yichen Li#, Yuxin Su, Pinjia He, Zifan Xie, and Michael R. Lyu. Proceedings of 38th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2023. - EvLog: Identifying Anomalous Logs over Software Evolution [PDF]
Yintong Huo, Cheryl Lee, Yuxin Su, Shiwen Shan, Jinyang Liu and Michael R. Lyu. Proceedings of 34th IEEE International Symposium on Software Reliability Engineering (ISSRE), 2023 - Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors [PDF]
Yun Peng, Shuzheng Gao, Cuiyun Gao, Yintong Huo, Michael R. Lyu. Proceedings of 44th International Conference on Software Engineering (ICSE), 2024 - CIKQA: Learning Commonsense Inference with a Unified Knowledge-in-the-loop QA Paradigm [PDF]
Hongming Zhang, Yintong Huo, Yanai Elazar, Yangqiu Song, Yoav Goldberg, Dan Roth. EACL Findings, 2023 - SemParser: A Semantic Parser for Log Analytics [PDF]
Yintong Huo, Yuxin Su, Baitong Li, Michael R. Lyu. Proceedings of 44th International Conference on Software Engineering (ICSE), 2023 - LogVM: Variable Semantics Miner for Log Messages [PDF]
Yintong Huo, Yuxin Su, Michael R. Lyu. Proceedings of 33rd International Symposium on Software Reliability Engineering (ISSRE), 2022 - LogPAI: An Open-Source Project for Automated Log Analysis [Project] [Announcement]
Pinjia He, Jieming Zhu, Shilin He, Zhuangbin Chen, Jinyang Liu, Yintong Huo, Yuxin Su, Zibin Zheng and Michael R. Lyu. IEEE SERVICES 2022 - IEEE Open Software Services Awards (3k+ Stars, 70k+ Downloads) - ARCLIN: Automated API Mention Resolution for Unformatted Texts [PDF]
Yintong Huo, Yuxin Su, Hongming Zhang, Michael R. Lyu. Proceedings of 44th International Conference on Software Engineering (ICSE), 2022. - Learning Contextual Causality Between Daily Events From Time-Consecutive Images [PDF]
Hongming Zhang, Yintong Huo, Xinran Zhao, Yangqiu Song, Dan Roth. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR Causality in Vision Workshop), 2021.
Honors and Awards
- ACM SIGSOFT CAPS Travel Grant: ASE'23, ICSE'24
- Nomination of Best Teaching Assistant Award, 2022
- IEEE Open Software Services Award, 2022
- Outstanding graduate of UESTC & Sichuan Province, 2020
- National Scholarship, 2019
- Outstanding Undergraduate Award, UESTC, 2017, 2018 & 2019
Services
- 2025: PC Member of ICSE
- 2024: PC Member of ICPE, ISSRE, FORGE (co-located with ICSE), Internetware (New Idea Track), Reviewer for TOSEM, Sub-reviewer for FSE
- 2023: PC Member of AIOPS Workshop (co-located with ICDE), Reviewer for TOSEM, STVR, Subreviewer for ISSRE, FSE, DSN, PRDC
- 2022: Subreviewer for ISSRE, FSE
- 2021: Subreviewer for ISSRE, DSN, WWW, APSEC
Teaching
At CUHK, I work as a teaching assistant for the following undergraduate courses:
- CSCI 3160 Algorithm Design and Analysis: Fall 2021, Spring 2020 (Nomination of the Best TA Award)
- CSCI 2100B Data Structure: Spring 2022
Experience
- 2019.09 - 2020.01, Research Assistant. KnowComp Group at Hong Kong University of Science and Technology with Prof. Yangqiu Song.
