Author

Guo-Wei Yang

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Preprint Aug 2026

Towards Effective Black-Box Adversarial Attacks on Deep Code Models via Structural and Identifier Perturbations

Deep code models (DCMs) are increasingly embedded in code intelligence tasks. However, their robustness under adversarial attacks remains insufficiently understood. Prior black-box attacks mainly rely on identifier- only substitutions or structural edits transferred from reference samples, yielding perturbation spaces...

Bin Duan, Jin-Tao Lin, D. Kim et al. · 0 citations

Preprint Aug 2026

Testing Deep Learning Library APIs via Cross-Framework Differential Fuzzing

Xamt, a cross-framework differential fuzzing approach for deep learning library APIs, constructs and tests execution-validated groups of APIs intended to implement equivalent operations across seven libraries.

Bin Duan, Rui Dong, Nai-Peng Dong et al. · 0 citations

Preprint Aug 2026

Harnessing LLMs for Document-Guided Fuzzing of Python Libraries

VistaFuzz is introduced, a document-guided fuzzing technique that uses a locally served open-sourced LLM to extract parameter specifications from API documents and generate inputs that satisfy both parameter constraints and inter-parameter dependencies.

Bin Duan, Tarek Mahmud, Meiru Che et al. · 0 citations