SDET Architecture & Core Practices

Automation must be accessible. I design frameworks where Functional Analysts can structure scenarios without deep programming knowledge.

How is this achieved?

• Logic Abstraction: Complex technical actions are reduced to readable Keywords or functions.
• Data Injection (Data-Driven): Separation of test data (JSON/CSV) from the script, allowing massive test iterations without duplicating code.
• High ROI: Facilitates long-term maintenance and speeds up the coverage of new business flows.

Structures built to dynamically adapt to the project's ecosystem through execution flags.

• Automatic base URL resolution mapped by environment (DEV, QA, STG, PROD).
• Configuration switches to inject the correct databases corresponding to the environment.
• Native safeguards to prevent accidental impacts on production databases.

Rigorous application of the Page Object Model and separation of concerns to withstand UI changes over time.

• Mapping Layer: Isolated Locators (CSS preferred over XPath for speed). If the DOM changes, only one file is edited.
• Business Layer: Classes/Keywords representing user actions and flows.
• Test Layer: Clean executable files containing assertions and business validation logic.

Implementation of Enterprise security practices (Basic DevSecOps).

• Strict use of environment variables and .env files (excluded via gitignore).
• Native support for credential injection via Pipeline secrets (Azure Key Vault / GitHub Secrets).
• Zero hardcoded tokens or passwords in the repository.

Solid experience unifying quality across multiple devices and platforms.

• Native and Hybrid automation using Appium (Android Studio / Xcode environments).
• End-to-End synchronization where a Web action triggers a Mobile App validation.
• Dynamic Desired Capabilities management for seamless integration with device farms.

Frameworks configured to provide actionable metrics without saturating CI/CD storage agents.

• Screenshots and DOM dumps captured exclusively when a test fails via Teardown Hooks.
• Smart overwriting to prevent gigabytes of useless historic images.
• Integration with advanced HTML reporting tools (Allure, ReportPortal) for executive dashboards.

UI tests are slow and brittle; I prioritize validation at lower layers following the Test Pyramid.

• Test data generation by directly injecting records via SQL (DBeaver/MySQL) or NoSQL (MongoDB).
• Validation of Status Codes and JSON schemas in microservices.
• UI bypass strategies (e.g., fetching OTPs directly from the database) to speed up regression tests.

Robust command-line interfaces to facilitate usage by DevOps and QA teams.

Enables isolating executions by tags (Smoke, Sanity, Regression) effortlessly.

Automation is incomplete until it lives inside the pipeline.

• Quality Gates: Blocking Pull Requests if critical tests fail.
• Scheduled nightly executions for deep unattended regressions.
• Solid experience integrating test suites into Azure DevOps and GitHub Actions environments.