# Case Study: Public-Safe QA Automation Framework

This case study describes a representative automation approach without exposing private code, real URLs, credentials, internal naming, customer data, or employer-specific details.

## Context

Modern product teams need fast feedback on critical journeys. A useful QA automation framework should make failures clear, keep scenarios readable, and produce evidence that product, development and QA can trust.

## Stack

- Playwright with TypeScript for browser automation.
- Cucumber/BDD for business-readable scenarios.
- Rest Assured and Postman-style checks for API validation.
- SQL validation notes for data integrity checks.
- Allure and Cucumber reports for evidence.
- Git and pull requests for reviewable change control.

## Approach

1. Map requirements into risks, acceptance criteria and regression priorities.
2. Create BDD scenarios for the highest-value user flows.
3. Keep selectors stable and page objects small.
4. Add API checks near UI workflows when backend behavior matters.
5. Capture screenshots, traces, logs and report artifacts for every critical failure.
6. Review flaky failures as framework quality issues, not just test execution noise.

## Example Public Flow

The demo flow uses a fictional checkout journey:

- Search public demo catalog.
- Add item to basket.
- Validate basket totals.
- Submit order to a mock endpoint.
- Verify confirmation status and evidence output.

## Why This Matters

Good automation is not just code. It is a communication layer between product expectations, engineering changes and release confidence.