Xiao Cheng
Xiao Cheng is a Post-Doctoral Researcher at School of Computer Science and Engineering,
University of New South Wales (UNSW), working with Scientia Associate Professor Yulei Sui.
His research lies at the intersection of Programming Languages (PL) and Software Engineering (SE), focusing on enhancing the security and reliability of modern software systems through software analysis and verification techniques,
including abstract interpretation, typestate analysis,
IFDS, and sparse value-flow analysis.
He is also exploring the integration of artificial intelligence, such as graph neural networks, language models
and uncertainty quantification, with classical PL/SE tasks to further enhance these domains.
His papers have been published in top-tier conferences and journals in the field of software engineering (TOSEM, FSE, ICSE, ISSTA), programming languages (OOPSLA) and security (TDSC), and awarded ACM SIGSOFT Distinguished Paper Award for FSE 2024 and ACM SIGPLAN Distinguished Paper Award for OOPSLA 2020.
He is one of the major contributors of the SVF project and the author of the DeepWukong project.
He has served as the web chair of LCTES 2024 and is serving or has served as artifact evaluation committee members for ICSE 2025, ISSTA 2024/2023, SAS 2023 and FormaliSE 2025/2024/2023, and PC member for ISSRE 2024 (DS track).
CV / Google Scholar / CMS Profile / Github / ORCID / Twitter
News
06/2024, We're honored to receive the Distinguished Paper Award at FSE. Thanks to the community for recognizing our work! 01/2024, Our work on quantum speedups on dynamic transitive closure-based static analysis accepted at TOSEM. 01/2024, Our work on path-sensitive typestate analysis accepted at FSE 2024. 12/2023, Our work on cross-domain abstract execution accepted at ICSE 2024.Publications
- CCF-A Dynamic Transitive Closure-Based Static Analysis through the Lens of Quantum Search
Jiawei Ren, Yulei Sui, Xiao Cheng, Yuan Feng and Jianjun Zhao
ACM Transactions on Software Engineering and Methodology (TOSEM) PDF BIB - CCF-A ACM SIGSOFT Distinguished Paper AWARD Fast Graph Simplification for Path-Sensitive Typestate Analysis through Tempo-Spatial Multi-Point Slicing
Xiao Cheng, Jiawei Ren, Yulei Sui
32nd ACM International Conference on the Foundations of Software Engineering (FSE '24) PDF Slides BIB - CCF-A Precise Sparse Abstract Execution via Cross-Domain Interaction
Xiao Cheng, Jiawei Wang, Yulei Sui
46th International Conference on Software Engineering (ICSE '24) PDF Slides BIB - CCF-C Vulnerability Detection via Typestate-Guided Code Representation Learning
Xiao Cheng
International Conference on Formal Engineering Methods (ICFEM '23) PDF BIB - CCF-A How About Bug-Triggering Paths? - Understanding and Characterizing Learning-Based Vulnerability Detectors
Xiao Cheng, Xu Nie, Ningke Li, Haoyu Wang, Zheng Zheng, Yulei Sui
IEEE Transactions on Dependable and Secure Computing (TDSC) PDF BIB - CCF-A Path-Sensitive Code Embedding via Contrastive Learning for Software Vulnerability Detection
Xiao Cheng, Guanqin Zhang, Haoyu Wang and Yulei Sui
The 31st ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA '22) PDF Slides BIB - CCF-A DeepWukong: Statically Detecting Software Vulnerabilities using Deep Graph Neural Network
Xiao Cheng, Haoyu Wang, Jiayi Hua, Guoai Xu and Yulei Sui
ACM Transactions on Software Engineering and Methodology (TOSEM) PDF BIB - CCF-A ACM SIGPLAN Distinguished Paper AWARD Flow2Vec: Value-Flow-Based Precise Code Embedding
Yulei Sui, Xiao Cheng, Guanqin Zhang and Haoyu Wang
Proceedings of ACM OOPSLA 2020 PDF BIB - CORE-A Static Detection of Control-Flow-Related Vulnerabilities Using Graph Embedding
Xiao Cheng, Haoyu Wang, Jiayi Hua, Miao Zhang, Guoai Xu, Li Yi and Yulei Sui
The 24th International Conference on Engineering of Complex Computer Systems (ICECCS 2019) PDF BIB
Services
Teaching Experience
Tools
(authored by Yulei Sui), a source code analysis framework that enables interprocedural dependence analysis for LLVM-based languages.
, a graph neural network based software vulnerability detector.