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LLM-Based Test Case Generation from Natural-Language Requirements: A Verified Multi-Domain Empirical Study with Symbolic Mutation Indicators

2026-06-23

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<title>Abstract</title> <p>Authoring test cases from natural-language requirements is a significant bottleneck in software quality engineering. We present an empirical evaluation of RAITG (Requirement-Aware Intelligent Test Generator), a four-stage LLM-based pipeline that decomposes a requirement into atomic units, expands each unit into structured test cases via a five-element prompt taxonomy, generates target-f...

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Literature Corpus work: 2036ae70-e16d-5259-894d-ddb42734d0df
DOI: 10.21203/rs.3.rs-10060668/v1

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