E-commerce applications demand reliable UI testing frameworks to ensure seamless functionality, improve user experience, and handle dynamic data scenarios. In this blog post, I’ll walk you through the journey of creating a robust, modular, and scalable UI testing framework for the Demoblaze e-commerce app using Playwright with Java. Along the way, I’ll share best practices for test automation, leveraging libraries like Faker for realistic data, and integrating CI/CD pipelines with GitHub Actions and Slack notifications.

Why Playwright for UI Testing?

Playwright, a modern, powerful end-to-end testing library, provides several advantages:

Multi-browser Support: Automates tests on Chromium, Firefox, and WebKit.
Headless/Headed Mode: Ensures flexibility for CI pipelines or local debugging.
Rich Features: Automatic waiting, screenshot capabilities, and network interception.
Cross-Language Support: Available in JavaScript, Python, Java, and .NET.

For this project, I chose Playwright with Java due to its compatibility with Java’s robust ecosystem and its seamless integration with test frameworks like TestNG.

🛠️The Framework Design:

A clean, scalable automation framework is critical for long-term success. My design incorporates:

1️. Page Object Model (POM)

The POM design pattern organizes the code base into modular components, making it easy to update locators and reuse functionality across tests.

2. Data-Driven Testing

Tests used the Faker library to dynamically generate realistic data such as names, emails, and passwords for different scenarios. And also used a properties file to set the test configuration like the browser type and setting the headless/headed mode.

3. Test Reporting

The framework integrates ExtentReports, which generates rich HTML reports with screenshots, and status summaries for easy debugging and tracking.

🧰Tech Stack Overview

The project leverages a modern and efficient technology stack for seamless test automation:

• Playwright: A robust browser automation library offering cross-browser testing capabilities. It's used to perform end-to-end UI testing across multiple platforms.

• Java (Version 17): The programming language chosen for its maturity, stability, and compatibility with test frameworks like TestNG.

• TestNG: A powerful testing framework to execute and organize test cases efficiently, especially for data-driven testing.

• Maven: A build and dependency management tool to streamline the project setup and integration of required libraries.

• Faker Library: Used for dynamic and realistic test data generation, including names, emails, and other random values.

• ExtentReports: Provides detailed and visually appealing HTML reports for tracking and analyzing test execution results.

This stack ensures the framework is scalable, modular, and easy to maintain while allowing for integration with CI/CD workflows and containerization using Docker.

🐳Docker Integration

One of the standout features of this project is the seamless integration with Docker, enabling the entire test framework to run in a containerized environment. To ensure environment consistency across machines, the framework is containerized using Docker.

How Docker is Used

• The project includes a Dockerfileand docker-compose.yml configuration for containerized test execution.

• A Docker container runs Playwright, Java 17, Maven, and all necessary dependencies to execute the test suite.

• Containers ensure cross-platform compatibility and scalability, allowing tests to run reliably on any machine.

Docker Compose File

Thedocker-compose.yml simplifies container orchestration. Here’s a snippet:

Running in Docker

Build and execute the container:
docker-compose up --build

Key Benefits of Docker in This Project

Isolation: Each test run occurs in a clean environment, avoiding conflicts with local dependencies.
Reproducibility: The Docker image defines a single source of truth for the environment, guaranteeing consistent results.
CI/CD Integration: Docker facilitates running the tests as part of a CI/CD workflow, ensuring seamless automation during code pushes or pull requests.

🔄Continuous Integration (CI) with GitHub Actions

I’ve integrated GitHub Actions to automatically execute tests on every code push or pull request for main branch.

GitHub Actions Workflow:

Here’s how the GitHub Actions look:

🔔Slack Notifications for Test Results

Using the slack GitHub Action, the framework sends test results to a Slack channel, ensuring real-time updates for the team.

Status: ✅ Success or ❌ Failure

Here’s how the notification looks:

📈Results and Advantages

• Scalable and Modular: With POM and TestNG, adding new test cases is straightforward.

• Dynamic Data Generation: Faker ensures diverse test scenarios with minimal effort.

• Seamless CI/CD: Automated workflows streamline the testing process, saving time.

• Real-Time Collaboration: Slack notifications keep the entire team updated.

🎯Key Takeaways

Building an automation framework for e-commerce requires careful consideration of modularity, scalability, and integration with modern tools. Using Playwright with Java, combined with data-driven testing and CI/CD workflows, ensures a robust and future-proof solution.

Feel free to explore the GitHub repository and raise any questions or suggestions!