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个人简介
I specialize in semantic modeling of source code with deep learning, software security, and program analysis. I work on bringing the power of them into making code bases secure, efficient, and defect-free.
As part of my most recent work (ICLR'22), I proposed a deep learning technique called CodeTrek that leverages relational databases to robustly represent code. The result is not only a uniform representation of any program information, but also the ability to use SQL-style queries to enrich that information. To better benefit from this rich structural and semantic information, I also developed a guided graph-walk mechanism to extract relevant context. CodeTrek's code understanding models are robust and better at predicting real-world bugs.
研究兴趣
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semanticscholar(2022)
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Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security (2022)
CCS '18: 2018 ACM SIGSAC Conference on Computer and Communications Security
Toronto
Canada
October, 2018pp.14-19, (2018)
Proceedings of the 2018 Workshop on Forming an Ecosystem Around Software Transformation - FEAST '18 (2018)
semanticscholar(2017)
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