About

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 in Digital Media Technology from the University of Electronic Science and Technology of China in 2020. My research focuses on Intelligence Software Engineering, which applies natural language processing techniques to facilitate software development, testing, and maintenance processes. The goal of my research is to ensure software reliability by enabling automated software reliability engineering over software lifecycles via data-driven approaches. Specifically, 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 with NLP techniques.
  • Software operation analysis: Identify, localize and analyze faults/anomalies in large cloud systems.
I am actively seeking faculty jobs worldwide! Feel free to reach out to me if you find my work interesting!

Below is my research framework towards data-driven automated software reliability engineering and current achievements. I am always open for any potential collaborators to discuss the relevant idea!

NEWS

  • [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.
  • [2023/07] Our paper "EvLog: Identifying Anomalous Logs over Software Evolution" has been accepted by 2023 ISSRE Research Track.
  • [2023/06/12] Our paper "Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors" has been accepted by 2024 ICSE Technical Track.
  • [2022/12/10] Our paper "SemParser: A Semantic Parser for Log Analytics" has been accepted by 2023 ICSE Technical Track.

Publication

  • DivLog: Log Parsing with Prompt Enhanced In-Context Learning
    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

  • 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, Sub-reviewer for FSE
  • 2023: PC Member of AIOPS Workshop, 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