01 • Purpose
Why do teams automate tests?
Automation executes repeatable checks quickly and consistently. It helps teams detect regressions, validate important workflows, and receive fast feedback when software changes.
Humans still explore, assess usability, investigate risks, interpret failures, and decide what quality means for the customer.
02 • Test Selection
Choose valuable candidates
Good automation candidates are stable, repeatable, and valuable to run frequently.
Critical paths, regression checks, data-driven tests, and cross-browser checks.
Frequently changing interfaces or scenarios with complicated setup.
New features, visual judgment, usability, and unexpected behavior.
Customer impact, business importance, failure frequency, and execution cost.
03 • Tools
Playwright and Selenium
Both tools automate browser interactions. The right choice depends on the product, team skills, browser requirements, and existing test ecosystem.
- Playwright: modern browser automation, auto-waiting, tracing, and multi-browser support.
- Selenium: mature WebDriver ecosystem with broad language and browser support.
- API testing: validates services faster and below the user-interface layer.
- Mobile tools: Appium and platform tools support native mobile automation.
04 • Test Design
Create reliable automated checks
Avoid flaky tests
A flaky test passes and fails without a meaningful product change. Common causes include timing problems, shared data, unstable selectors, test-order dependencies, and inconsistent environments.
05 • Delivery Workflow
Connect tests to Git and CI/CD
Git records changes to test code. A CI/CD pipeline can install dependencies, run checks, publish results, and prevent risky changes from moving forward.
Developer opens a pull request → build starts → automated checks run → results are reported → team reviews failures.
06 • AI Assistance
Use AI with human review
AI can help generate test ideas, draft code, explain failures, and summarize results. A QA engineer must still validate accuracy, security, maintainability, and whether the test proves meaningful behavior.
- Never paste secrets or private customer data into an unapproved tool.
- Review generated assertions and selectors before committing code.
- Run and debug every generated test.
- Treat AI output as a draft—not verified truth.
07 • Practice
Plan a small automation suite
Imagine an online ordering application. Select five tests for an initial automation suite. For each one, describe its value, required data, expected result, and whether it should run on every pull request or nightly.
08 • Knowledge Check