Abstract:Deep learning has been widely used to solve various code-based tasks by building deep code models based on a large number of code snippets. However, deep code models are still vulnerable to adversarial attacks. As source code is discrete and has to strictly stick to the grammar and semantics constraints, the adversarial attack techniques in other domains are not applicable. Moreover, the attack techniques specific to deep code models suffer from the effectiveness issue due to the enormous attack space. In this… Show more
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