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Airbnb Uses LLMs to Pull Off an 18-Month Enzyme to RTL Migration in Just 6 Weeks
- Airbnb successfully migrated around 3,500 React component test files from Enzyme to React Testing Library (RTL) in just 6 weeks using LLMs and robust automation.
- The company aimed to modernize React testing practices and move away from Enzyme's deep access to component internals.
- Airbnb's LLM-driven migration involved breaking down the process into automated validation and refactoring steps, leading to the migration of 75% of target files in four hours.
- The company experimented with prompt engineering and a brute-force retry loop to improve migration success, resulting in 97% completion after four days.
- Google also saw success with LLM-driven migrations, achieving a 50% improvement in speed in code transformations like converting unique ID types.
- An AWS study on human-AI partnership in code migrations found that developers view AI as a collaborative teammate but prefer control over the process.
- Developers desire to guide and review the AI based on their expertise, serving as reviewers to ensure accurate changes during the migration process.
- However, there is still a need for human oversight, review, and verification in LLM-driven code migrations to address potential errors and ensure accurate outcomes.
- Airbnb's success with LLMs in code migration showcases the potential for AI-driven solutions in accelerating and improving the efficiency of complex software migration tasks.
- Google and AWS have also demonstrated successful implementations of LLMs in code migrations, highlighting the benefits of combining AI with human expertise.
- While AI-driven migrations offer significant speed and efficiency advantages, developers emphasize the importance of maintaining control and verification throughout the process.
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