An AI-native academic-writing platform I founded and lead, pairing LLM agents with real-time collaborative LaTeX editing. It now serves 2,000+ users on a paid-subscription model, with multi-agent workflows spanning the full paper lifecycle: literature search, outlining, drafting, data analysis, and revision.
A research line on binary SCA that detects third-party libraries and known vulnerabilities directly in compiled C/C++ binaries. It powers BLADE, an evidence-based detection framework integrated into a commercial SCA product for compliance checks in regulated industries such as automotive.
Published in ICSE, 2023
Precise and scalable C/C++ third-party library detection using fingerprinting functions.
Recommended citation: J. Wu, Z. Xu, W. Tang, L. Zhang, Y. Wu, Chengyue Liu, et al. (2023). "Ossfp: Precise and Scalable C/C++ Third-Party Library Detection Using Fingerprinting Functions." IEEE/ACM International Conference on Software Engineering (ICSE 2023).
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Published in FSE, 2025
A database-less Software Composition Analysis approach for identifying third-party reuse.
Recommended citation: L. Zhang, J. Wu, S. Zhang, Chengyue Liu, et al. (2025). "Drop the Golden Apples: Identifying Third-Party Reuse by DB-Less Software Composition Analysis." Proceedings of the ACM on Software Engineering (FSE 2025).
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Published in ASE, 2025
Recovering binary data structures by combining static analysis with semantic information.
Recommended citation: Y. Zhang, Z. Xu, Z. Lang, Chengyue Liu, et al. (2025). "BinStruct: Binary Structure Recovery Combining Static Analysis and Semantics." IEEE/ACM International Conference on Automated Software Engineering (ASE 2025).
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Published in ISSTA, 2026
BLADE, an evidence-based detection framework replacing similarity-score heuristics with multi-source LLM-guided verification; 97.60% precision / 93.74% recall.
Recommended citation: Chengyue Liu, et al. (2026). "Beyond Similarity Scores: Evidence-Based Third-Party Library Detection for C/C++ Binaries." Proceedings of the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2026). ACM SIGSOFT Distinguished Paper Award.
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Published in ISSTA, 2026
An empirical study of synchronization gaps, delays, and missed opportunities across software forks.
Recommended citation: J. Zhu, L. Zhang, J. Wu, Chengyue Liu, Y. Liu. (2026). "Mind the Gap: An Empirical Study of Synchronization Gaps, Delays, and Missed Opportunities in Software Forks." Proceedings of the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2026).
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Published in OOPSLA, 2026
XLoc localizes functions in binaries directly from source code with no compilation required. (Co-first author)
Recommended citation: J. Shi, Chengyue Liu*, et al. (2026). "From Similarity Ranking to Definitive Verdict: LLM-Enhanced Source-to-Binary Function Localization." Proceedings of the ACM on Programming Languages (OOPSLA 2026). *Co-first author.
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Published in ASE, 2026
First large-scale empirical study of NPM malicious package detection, evaluating 11 tools with 16 variants on a unified benchmark of 6,420 malicious and 7,288 benign packages.
Recommended citation: W. Guo, Z. Chen, Z. Xu, C. Liu, M. Kang, S. Song, Chengyue Liu, et al. (2026). "How Effective Are NPM Malicious Package Detectors? A Large-Scale Empirical Study." IEEE/ACM International Conference on Automated Software Engineering (ASE 2026).
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Published in FSE, 2026
First large-scale empirical study of binary SCA tools, benchmarking 11 tools across 38,228 test cases over 1,873 libraries.
Recommended citation: Chengyue Liu, et al. (2026). "Understanding the Limitations of C/C++ Binary Third-Party Library Detection Tools: An Empirical Study at Scale." Proceedings of the ACM on Software Engineering (FSE 2026).
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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