TestHumanizer uses LLMs as refactoring layers on EvoSuite suites to reach 88-98% compilation rates and better readability on 350 classes from Defects4J and SF110 while preserving coverage.
Leveraging large language models for enhancing the under- standability of generated unit tests
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MUTGEN incorporates mutation feedback into LLM prompts and uses iteration to generate unit tests that achieve higher mutation scores than EvoSuite or vanilla LLM prompting on 204 benchmark subjects.
citing papers explorer
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Humanizing Automatically Generated Unit Test Suites with LLM-Based Refactoring
TestHumanizer uses LLMs as refactoring layers on EvoSuite suites to reach 88-98% compilation rates and better readability on 350 classes from Defects4J and SF110 while preserving coverage.
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Mutation-Guided Unit Test Generation with a Large Language Model
MUTGEN incorporates mutation feedback into LLM prompts and uses iteration to generate unit tests that achieve higher mutation scores than EvoSuite or vanilla LLM prompting on 204 benchmark subjects.