Why is a large-scale test framework migration usually so slow to do by hand?
Two testing frameworks like Enzyme and React Testing Library operate at different levels of abstraction — one inspects component internals, the other tests from a user's perspective — so tests can't be translated line-for-line. Every file needs structural understanding, not mechanical find-and-replace, which is exactly the kind of judgment-heavy, repetitive work that eats engineering-years at scale.
Answered in
How to Migrate Thousands of Legacy Test Files With LLMs, Not RewritesA step-based pipeline, retry loops instead of perfect prompts, and rich context injection turn a year-long manual migration into a six-week automated one.
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More development best practices questions
- Why did retry loops with error feedback outperform carefully engineered prompts?
- When does a migration pipeline need rich prompt context instead of just retries?
- How do you migrate the last 3% of files that automation can't fully finish?
- Does this approach only work for test framework migrations?
- What is Project Polaris and how does it relate to GitHub Copilot?
- What architecture does Project Polaris use?
- How does Project Polaris perform compared to GPT-4 Turbo on coding benchmarks?
- Can teams still use GPT-4 Turbo in Copilot after the Polaris rollout?
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