GraphCodeBERT uses data flow graphs in pre-training to capture semantic code structure and reaches state-of-the-art results on code search, clone detection, translation, and refinement.
Exploring software natural- ness throughneural language models
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VulStyle pre-trains on 4.9M functions using code, non-terminal ASTs, and stylometry features, then fine-tunes to achieve SOTA F1 gains of 4-48% on BigVul and VulDeePecker.
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GraphCodeBERT: Pre-training Code Representations with Data Flow
GraphCodeBERT uses data flow graphs in pre-training to capture semantic code structure and reaches state-of-the-art results on code search, clone detection, translation, and refinement.
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VulStyle: A Multi-Modal Pre-Training for Code Stylometry-Augmented Vulnerability Detection
VulStyle pre-trains on 4.9M functions using code, non-terminal ASTs, and stylometry features, then fine-tunes to achieve SOTA F1 gains of 4-48% on BigVul and VulDeePecker.