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Slack Combines ASTs with LLMs to Automatically Convert 80% of 15,000 Unit Tests
Slack's engineering team recently published how it used a large language model (LLM) to automatically convert 15,000 unit and integration tests from Enzyme to React Testing Library (RTL). By combining Abstract Syntax Tree (AST) transformations and AI-powered automation, Slack's innovative approach resulted in an 80% conversion success rate, significantly reducing the manual effort required.
The conversion tool's adoption rate at Slack reached approximately 64%, saving considerable developer time of at least 22% of 10,000 hours. Gorbachov notes that "the outcomes ranged from remarkably effective conversions to disappointingly inadequate ones, depending largely on the complexity of the task." Slack's engineers then adopted a hybrid approach, combining the AST transformations with LLM capabilities and mimicking human behaviour.
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