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QA automation kursu test avtomatlaşdırma üzrə praktiki bacarıqlar qazandırır: test skriptlərinin dizaynı, framework-lərin qurulması və icrası. Real layihələr üzərində software testing və avtomatlaşdırılmış test yanaşmaları ilə keyfiyyəti yüksəltməyi və çatdırılma sürətini artırmağı öyrənirsiniz.
Modullar sürətli baxış üçün yığcam qalır. Mövzularına baxmaq üçün istənilən modulu açın.
- Variables, control flow, and Object-Oriented Programming
- Collections (Lists, Maps, Sets)
- Exception handling and file handling
- The TDD workflow: Red → Green → Refactor
- Writing the test before the implementation — and letting it fail on purpose
- Making it pass with the simplest possible code
- Refactoring for design quality while keeping every test green
- JUnit 5 as the vehicle for practicing TDD: annotations, assertions, test lifecycle
Project Checkpoint: Business Logic Library (built TDD-first): starting from nothing but failing tests, grow a small real Java library that mirrors a real web project's business rules (e.g. a shopping-cart pricing/discount engine). No Selenium yet — t
- Branching strategies, pull requests, resolving merge conflicts
- Collaborative workflows on a shared automation repository
- Project structure and dependency management
- Running and organizing test execution through a build tool
- SOLID principles applied to test automation code
- Design patterns automation frameworks actually use: Singleton (driver management), Factory, Builder, Strategy
- The Page Object Model (POM) and Page Factory as the core structural pattern
- Layered framework architecture: config, driver management, page objects, utilities, tests, reporting
Project Checkpoint: Framework Skeleton v1: before writing a single Selenium test, scaffold the layered, SOLID-compliant repository structure that every later project plugs into.
- WebDriver architecture, CSS/XPath locators
- Waits and synchronization strategies
- Handling frames, alerts, dropdowns, and multiple windows
- Handling frames, alerts, dropdowns, and multiple windows
Project Checkpoint: Web Automation Project: automate 10+ real user journeys (login, search, cart, checkout) on saucedemo.com inside the framework skeleton.
- Annotations, execution order, and parameterization
- Suites, parallel execution, and assertions
- Playwright architecture vs. Selenium: auto-waiting, tracing, browser contexts
- Hands-on: porting several SauceDemo journeys from Selenium to Playwright
- Awareness note: visual regression testing with Applitools/Percy — why pixel/DOM diffing catches what functional tests miss
AI Spotlight: Live demo: Playwright MCP — letting an AI agent (Claude, Copilot) drive a real browser through natural-language instructions instead of hard-coded steps.
- Appium server and Inspector, Desired Capabilities, UiAutomator2 (Android) and XCUITest (iOS)
- Native, hybrid, and mobile web app testing across both platforms
- Documenting platform-specific locator and capability differences inside the shared framework
AI Spotlight: Live demo: Appium MCP driving Android and iOS apps through natural-language instructions.
Project Checkpoint: Mobile Automation Project: automate real scenarios (gestures, deep links, native alerts) on Sauce Labs' My Demo App for both Android and iOS, inside the shared framework.
- Gherkin syntax and feature files
- Step definitions and framework integration
Project Checkpoint: Rewrite the SauceDemo checkout journey as a Gherkin feature file, wired into the existing Selenium/POM framework.
- Setup, HTTP methods, request/response validation
- Authentication, serialization/deserialization, JSONPath
- API assertions and framework structure
AI Spotlight: Bridging the gap: draft an assertion in Postbot first, then translate that logic into a proper REST Assured test method.
Project Checkpoint: API Automation Project: automate the Petstore/restful-booker scenarios in REST Assured and fold the API layer into the same shared framework used for Web and Mobile.
- How self-healing works conceptually (and why free Healenium ≠ Healenium Pro's built-in AI)
AI Spotlight: Bonus lab: build a custom self-healing mechanism — catch a broken locator exception, send the surrounding DOM to an OpenAI endpoint, retry with the suggested selector, and log every healing event as an Allure step.
- Why GitLab CI/CD for a training environment: free tier, no self-hosted server to maintain, `.gitlab-ci.yml` in the same repo as the framework
- Pipeline stages, jobs, scheduling and triggering test runs
- Brief awareness: GitHub Actions and Jenkins — what you'll likely meet on the job
Project Checkpoint: Framework goes CI: wire the Web, API, and Mobile suites into one GitLab CI/CD pipeline, running on every push and on a nightly schedule.
- Allure and Extent Reports
- Publishing reports and healing-event logs as GitLab CI pipeline artifacts
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