Twitter Space | Testing: unit (testing-library/react) and end-to-end/integration

Key takeaways
  1. AI in testing: AI can be used to write test assertions for visual testing and generate test code, but it should be used with caution and double-checked to ensure accuracy.
  2. 100% code coverage: While 100% code coverage is often seen as a goal, it may not be necessary or even desirable in all cases. It can lead to useless tests and a false sense of security.
  3. Testing for change: Tests should be designed to be resilient to change, so that they don’t need to be constantly updated as the codebase evolves.
  4. Visual testing: Visual testing tools can be helpful for catching UI bugs that might be missed by traditional unit tests.
  5. End-to-end tests: End-to-end tests are important for ensuring that the entire application works as expected, but they can be slow and expensive to run.
  6. Testing in production: Some companies run tests in production to catch regressions and ensure that new features don’t break existing functionality.
  7. AI-assisted testing: AI can be used to help with testing tasks such as generating test data, identifying flaky tests, and repairing broken tests.
  8. Optimizing for scale: As applications grow in size and complexity, it becomes important to optimize the testing process to make it faster and more efficient.
  9. Use case coverage: Instead of focusing on achieving a certain percentage of code coverage, it’s more important to focus on testing the most critical use cases and ensuring that the tests are effective.
  10. Testing as a mindset: Testing should be seen as an integral part of the development process, not just a chore that is done at the end.