2305.08360.pdf

- Evaluating ChatGPT on CodeXGlue dataset for code generation tasks. - Proposing prompt design and optimization methods for better code generation.

– Evaluating ChatGPT for code generation tasks
– Proposing prompt design and optimization methods

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– ChatGPT is a language model used for generating human-like responses.
– ChatGPT was evaluated for code generation tasks using the CodeXGlue dataset.
– The prompt design was found to significantly improve the generation performance.
– The performance of the best prompts was compared with state-of-the-art finetuned LLMs.
– CodeBLEU was used as the overall evaluation metric for code generation.

– Improved prompts for guiding ChatGPT in code generation.
– Evaluation of ChatGPT’s performance on CodeXGlue dataset.

– Evaluating ChatGPT on CodeXGlue dataset for code generation tasks.
– Proposing prompt design and optimization methods for better code generation.

– Prompts improved ChatGPT’s code generation performance substantially.
– Factors influencing prompt design for code generation tasks were analyzed.

– Experimental settings and results for four research questions.
– Comparison with benchmark models and related works.