Large language models struggle with generating clean code
Explore how large language models struggle with clean code generation, revealing high API misuse and the need for better reliability assessments.
The article discusses a study on the reliability and robustness of code generated by large language models (LLMs) for Java coding questions. The study evaluated four code-capable LLMs, including GPT-3.5 and GPT-4 from OpenAI, and found that they exhibited high rates of API misuse. The study also highlighted the importance of assessing code reliability beyond semantic correctness and emphasized the need for static analysis to ensure full coverage. Llama 2, an open model, performed the best with a failure rate of less than one percent.
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