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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
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