Sakura is a multi-agent system that generates structurally complex tests from NL descriptions, achieving 50-78% higher compilability and 38-66% higher coverage overlap than baselines on 1,464 scenarios from 20 Apache Commons applications.
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The paper introduces a red-train-green lifecycle and governance metric stack that adapts acceptance testing to LLM systems for business use.
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Sakura: An Approach for Generating Complex Tests from Natural Language Test Descriptions
Sakura is a multi-agent system that generates structurally complex tests from NL descriptions, achieving 50-78% higher compilability and 38-66% higher coverage overlap than baselines on 1,464 scenarios from 20 Apache Commons applications.
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Acceptance-Test-Driven Evaluation Protocols for Business-Centric LLM Systems
The paper introduces a red-train-green lifecycle and governance metric stack that adapts acceptance testing to LLM systems for business use.