AI RESEARCH
Security and Quality in LLM-Generated Code: A Multi-Language, Multi-Model Analysis
arXiv CS.LG
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ArXi:2502.01853v2 Announce Type: replace-cross Artificial Intelligence (AI)-driven code generation tools are increasingly used throughout the software development lifecycle to accelerate coding tasks. However, the security of AI-generated code using Large Language Models (LLMs) remains underexplored, with studies revealing various risks and weaknesses. This paper analyzes the security of code generated by LLMs across different programming languages. We