Testing
Running Detox tests in CI requires matching simulator/emulator availability to your runner OS, caching dependencies, and handling the slow parts (app builds, simulator boot) efficiently. This guide covers complete CI configurations for GitHub Actions and GitLab CI for both iOS and Android. Key Takeaways * iOS requires macOS runners — this
Testing
Flaky Detox tests almost always come from one of three sources: broken synchronization (the app isn't idle when Detox thinks it is), poor test isolation (state from one test bleeds into the next), or incorrect element selectors (the testID you're targeting doesn't exist in
Testing
qTest reporting converts raw test execution data into information that QA leads, project managers, and executives can act on.
Next.js
Unit tests verify that individual functions and components work correctly.
Python
Behave and the Python requests library are a natural pairing for API testing. You write scenarios in plain Gherkin that non-developers can read, while step definitions handle the HTTP calls. This post walks through project setup, reusable context objects, authentication flows, and error-case testing — all with working code.
Testing
The RAG evaluation tooling landscape has exploded. RAGAS, TruLens, DeepEval, UpTrain, Arize Phoenix — there are at least a dozen frameworks claiming to be the definitive way to measure RAG quality. Evaluating the evaluators is its own non-trivial problem. Most teams pick the first framework they encounter, discover it does
Testing
At 10 tests, test data management is easy. You have a few fixture files, maybe a before_each that resets a table or two, and everything works.
Testing
SLOs and SLAs describe what your system promises. Tests verify whether those promises hold.
Testing
Integration tests are slow, brittle, and expensive to maintain. You spin up multiple services, wire them together in a test environment, and hope that everything behaves the way it did last Tuesday. When a test fails, you spend twenty minutes figuring out whether the problem is in the consumer, the
Testing
Flaky tests are a design problem, not a tooling problem. The most sophisticated CI infrastructure won't make a fundamentally non-deterministic test reliable. The solution is to design tests so they can only produce one result: pass when the application works correctly, fail when it doesn't.
Testing
Example-based testing asks "does this specific input produce this specific output?" Property-based testing asks "does this output have this characteristic for all possible inputs?" Property testing generates hundreds of random examples and finds the edge cases you wouldn't think to write manually.
Ruby on Rails
RSpec shared examples and shared contexts eliminate massive test duplication when multiple models or controllers share the same behavior. This post covers advanced patterns including custom matchers, metadata tagging, and composable shared contexts that scale across large Rails codebases. Test suites grow fast. A Rails app with a dozen models,