Refusing the Impossible: A Taxonomy and Benchmark for Code Hallucination in Large Language Models

Large language models (LLMs) often produce code that looks plausible but is not grounded in reality. The code may import packages that do not exist or claim to implement algorithms that violate proven theorems, while still compiling and running. We study \emph{code hallucination} as \emph{ungrounded