Page 14 - Testing/E2E

Vitest UI replaces plain terminal output with an interactive dashboard in the browser, complete with test filtering, module graph, coverage heatmap and snapshot diffs at a glance. Anyone regularly searching through hundreds of tests in a Vue project finds failing cases and untested code paths much faster with Vitest UI than by scrolling through console logs.

Integration and end-to-end tests rarely fail because of the test logic itself, they fail because of the environment: the wrong database version, services that never started, race conditions during startup. Docker Compose solves exactly that, with declared dependencies, healthchecks and network isolation that make every test run reproducible.

An OpenAPI specification that exists only for documentation does not get you very far. Anyone who treats it as a binding contract between frontend, backend and external consumers, and hardens it with contract tests, RFC 7807 error formats, security schemas and automated tooling, turns a YAML file into a genuinely productive quality tool.

Testing Magento checkout flows only against the real API gives you slow, flaky end-to-end tests that turn red on every backend hiccup. With cy.intercept() you stub and observe network requests on purpose, load fixtures for realistic responses, and test error and loading states deterministically, without ever touching a real server. That keeps your tests fast, reproducible, and independent of the current database state.

Anyone who simply overwrites globalThis.fetch in unit tests builds fragile mocks that need adjusting with every code change. Mock Service Worker instead intercepts network requests at the HTTP level, exercises the real fetch call, and can be configured precisely for both success and error cases without touching the application code itself.

Anyone who only ever runs tests and CLI commands in the terminal loses valuable seconds on every cycle. Run configurations in PhpStorm turn the green play button into a real tool, with a Docker interpreter, Xdebug integration and compound runs for complex workflows.

A test is only as meaningful as the data it runs on. Claude helps with test data generation by producing realistic, structurally consistent, and deliberately faulty datasets, from single fixtures to bulk data for performance tests, without ever using real customer data.

Validation in GraphQL is not a single mechanism but an interplay of schema types, custom scalars, resolver logic and explicit error types. Anyone who relies on just one layer ends up with incomplete validation. This article shows how all the layers work together and which mistakes typically occur.

API reviews without a systematic checklist consistently miss the same categories: security aspects, error formats, performance and test coverage tend to get skipped under time pressure. A structured checklist makes reviews faster, more complete and repeatable, and ensures that no PR gets merged with a critical gap.

Flaky tests are end-to-end tests that pass sometimes and fail other times without any code change, and they undermine trust in the entire test suite. The causes almost always come down to timing issues, shared test state, network dependencies or fragile selectors. This article shows how to systematically find these root causes, apply robust Cypress and Playwright patterns, and quarantine flaky tests in a controlled way instead of silently ignoring them.