Kaifeng Huang - 黄凯锋
Kaifeng Huang is an Assistant Professor (tenure-track) at School of Computer Science and Technology, Tongji University. Prior to that, he was a research fellow at Software Engineering Lab, Fudan University. He obtained his PhD from Fudan University in 2022.
His research interests focus on malleable software, software/AIware supply chain, and software security. He serves in the reviewer panels and program committees of IEEE Transactions on Software Engineering, ACM Transactions on Software Engineering and Methodology, ICSE 2027, FSE 2026, Journal of Systems & Software, ASE 2025/2024, ISSRE 2024, ICSE AE 2023, etc. He received the distinguished reviewer award at ASE 2025. He was the awardee of the ACM SIGSOFT Distinguished Paper Award at ASE 2018 and IEEE TCSE Distinguished Paper Award at ICSME 2020.
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Research Interests
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Malleable Software. As LLMs continue to improve in coding tasks, they enable a new paradigm of malleable software where systems are not rigidly predefined but can dynamically evolve to meet user expectations and adapt to diverse execution environments. This emerging paradigm opens up many fundamental and still unresolved challenges. My research aims to advance and ensure software quality and trustworthiness in this emerging paradigm.
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Trustworthy Software & AI Supply Chains. My research aims to ensure the trustworthiness of software and AI supply chains by assessing their security, maintenance, and legal risks , while developing effective mitigation strategies . This work spans key areas including third-party library dependencies ( EMSE'22 , ICSME'20 ), dependency-related bugs in deep learning systems ( FSE'23 ), LLM pre-training membership inference risks ( AAAI'26 ), open-source license compliance ( ISSTA'24 ), API deprecation ( ASE'21 , ICSE'25 ), API compatibility ( JOS'24 ), library version evolution ( FSE'20 ), and software/code differences ( ASE'18 , ICSE'20 ).
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Software Security. Software systems are inherently vulnerable to security threats. My research focuses on, but is not limited to areas such as vulnerability detection, assessment, and mitigation , malicious software/data detection , and privacy protection . This work spans key topics including recurring vulnerability detection ( CCS'24 ), vulnerability database quality ( FSE'22 , ICSE'24 , ASE'24 ), and malicious packages in ecosystems such as PyPI and NPM ( TOSEM'25 , USENIX Security'25 , ASE'24 ).
Highlights
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VMUD: Detecting Recurring Vulnerabilities with Multiple Fixing Functions via Function Selection and Semantic Equivalent Statement Matching.
Kaifeng Huang
, Chenhao Lu, Yiheng Cao, Bihuan Chen, Xin Peng.
In Proceedings of the 31th ACM Conference on Computer and Communications Security, Salt Lake City, United States, accepted, 2024.
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Vision: Identifying Affected Library Versions for Open Source Software Vulnerabilities.
Susheng Wu, Ruisi Wang,
Kaifeng Huang
, Yiheng Cao, Wenyan Song, Zhuotong Zhou, Yiheng Huang, Bihuan Chen, Xin Peng.
In Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering, Sacramento, California, United States, pp. 1447-1459, 2024.
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Identifying Affected Libraries and Their Ecosystems for Open Source Software Vulnerabilities.
Susheng Wu, Wenyan Song,
Kaifeng Huang
, Bihuan Chen, Xin Pen.
In Proceedings of the 46th
IEEE/ACM International Conference on Software Engineering (ICSE), Lisbon, Portugal, pp. 162: 1-12, 2024.
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