On a custom Python shopping-cart benchmark, docstrings substantially improve LLM-generated unit tests, full implementations add little, and chain-of-thought prompting yields the highest branch and mutation scores.
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Impact of Code Context and Prompting Strategies on Automated Unit Test Generation with Modern General-Purpose Large Language Models
On a custom Python shopping-cart benchmark, docstrings substantially improve LLM-generated unit tests, full implementations add little, and chain-of-thought prompting yields the highest branch and mutation scores.