Sitemap
A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
Xept — Academic Writing AI-Agent Permalink
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.
Binary Software Composition Analysis
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.
publications
Ossfp: Precise and Scalable C/C++ Third-Party Library Detection Using Fingerprinting Functions
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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Drop the Golden Apples: Identifying Third-Party Reuse by DB-Less Software Composition Analysis
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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BinStruct: Binary Structure Recovery Combining Static Analysis and Semantics
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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Beyond Similarity Scores: Evidence-Based Third-Party Library Detection for C/C++ Binaries
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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Mind the Gap: An Empirical Study of Synchronization Gaps, Delays, and Missed Opportunities in Software Forks
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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From Similarity Ranking to Definitive Verdict: LLM-Enhanced Source-to-Binary Function Localization
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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How Effective Are NPM Malicious Package Detectors? A Large-Scale Empirical Study
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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Understanding the Limitations of C/C++ Binary Third-Party Library Detection Tools: An Empirical Study at Scale
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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talks
Talk 1 on Relevant Topic in Your Field
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This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.