SeGa extracts business semantics from requirements to generate unit tests that detect 22-25 more real-world business logic bugs than prior LLM-based methods in industrial Go projects.
Chatunitest: a chatgpt- based automated unit test generation tool,
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A black-box LLM approach for fault localization in system-level test code that estimates execution traces from failure logs to rank potential faults with reduced inference cost.
Frontier LLMs achieve only moderate performance on multi-file unit test generation, with basic executability and cascade errors common, but manual and self-error-fixing mechanisms yield measurable gains.
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Uncovering Business Logic Bugs via Semantics-Driven Unit Test Generation
SeGa extracts business semantics from requirements to generate unit tests that detect 22-25 more real-world business logic bugs than prior LLM-based methods in industrial Go projects.
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Efficient Black-Box Fault Localization for System-Level Test Code Using Large Language Models
A black-box LLM approach for fault localization in system-level test code that estimates execution traces from failure logs to rank potential faults with reduced inference cost.
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MultiFileTest: A Multi-File-Level LLM Unit Test Generation Benchmark and Impact of Error Fixing Mechanisms
Frontier LLMs achieve only moderate performance on multi-file unit test generation, with basic executability and cascade errors common, but manual and self-error-fixing mechanisms yield measurable gains.