TestDriveSelenium

Focused on UI test automation with Selenium WebDriver, applying DDT by separating test logic from test data.

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At a Glance

UI Automation with Selenium WebDriver

• Clear separation between pages, actions and tests
• Behavior-oriented test scripts
• Scalable and maintainable folder structure

Data-Driven Testing (DDT)

• Test logic isolated from test data
• Externalized inputs (CSV / JSON / Python dictionaries)
• Flexible scenario variations

Page Object Model (POM)

• Centralized locators
• Reusable page actions
• Consistent naming and design conventions

Python Ecosystem

• Selenium WebDriver
• Pytest
• Robot Framework (complementary keyword layer)

CRM-style Workflows

• Generic patterns inspired by Salesforce : authentication, navigation, case management

Tech Stack

• Language : Python
• Automation : Selenium WebDriver
• Test Runners : Pytest, Robot Framework
• Design Pattern : Page Object Model (POM)
• Data Formats : CSV, JSON, Python dictionaries
• Target Workflows : CRM-style UI interactions
• IDE : PyCharm

Structure

├─ 📁 docs/ → Test plans, workflows, guidelines
├─ 📁 scripts/ → Automated test scripts and framework logic
├─ 📁 examples/ → Sample test data and anonymized DDT inputs
├─ 📁 reports/ → Execution logs and result reports (traceability)
└─ README.md

Files Structure Color-Coded :
🟦 Architecture & Strategy
High-level design, layers, framework, roadmap
🟩 Operational Guidelines
POM & DDT best practices, naming, logging, maintainability
🟪 Concrete Test Plans
Actual test plans, workflows, scripts, test data

🔗 Related Repositories

jobs:
  - name: DeploymentPlaybook
    role: Deployment procedures & verification (IDM, Salesforce, CI/CD)
    repo: github.com/LoubnaEA/DeploymentPlaybook

  - name: TestTrekker
    role: Test plans, workflows & automation scripts
    repo: github.com/LoubnaEA/TestTrekker

TestDriveSelenium
├── uses → DeploymentPlaybook : deployment & verification
└── uses → TestTrekker : test plans & workflows

Notes

Data-driven UI automation in a CRM-like environment.
All workflows and datasets are anonymized and generic.
Focus on :
-- Test design quality
-- Automation architecture
-- Maintainability and scalability