Revolutionizing UI Testing: The Power of GenAI Tools

Introduction

As SDET frontend engineers, we hold the crucial responsibility of ensuring the quality of customer-facing products across diverse browsers and platforms. The challenge grows when catering to a large user base spread across multiple configurations, making it difficult to manually test every combination. Add to this the need to support even niche traffic — such as 10% of users on specific platforms will required setups on local environment to run / validate the executions and the task becomes increasingly complex.

The Challenge of In-Built Browsers

Social media platforms like Instagram and Facebook drive significant traffic but bring their own set of challenges. Testing applications on their in-built browsers is not straightforward, especially with current Selenium WebDriver setups, which primarily support web, Android, iOS, and mobile web browsers. To ensure these platforms are covered in every regression cycle, we often rely on manual or automated tests — both of which come with their own set of hurdles.

Cross-Platform Testing Pain Points

Testing on mobile browsers, Android SDK, and iOS SDK platforms presents unique challenges. While writing test scripts isn’t the issue, maintaining them is. False failures, updates to XPath, and changes in user journeys require constant updates. This often necessitates tools like XCode and Android Studio, which can be resource-intensive and time-consuming, especially when managing a large test suite.

Exploring GenAI Tools

Given these challenges, we explored GenAI tools like TestTrigor, TestSigma, and BrowserStack’s LCNC (Low-Code/No-Code) solutions. These tools aim to streamline the QA process, reducing the pain points of maintaining test scripts while supporting faster feature delivery.

Key Challenges with GenAI Adoption

1. Vendor Lock-In: Organizations may feel constrained by the solution, making future migration to another tool challenging.
2. Cost: Licensing fees for users and parallel runs can be expensive, making it a significant investment with inherent risks.
3. Impact on QA Roles: With GenAI tools offering features that reduce manual intervention, there’s a fear that QA/SDET roles might diminish, potentially being absorbed by developers or product teams.

Potential Benefits of GenAI Tools

1. Reduced Maintenance Costs: Debugging or updating scripts becomes simpler, requiring minimal local setup even for cross-platform products.
2. Adaptability to Evolving Products: As products evolve — often with significant UI updates every financial year — traditional test suites require rebuilding. GenAI tools can alleviate this burden, making vendor lock-in less of a concern.
3. Enhanced QA Role: While GenAI tools can handle E2E tests, QA engineers remain indispensable for designing user scenarios from a customer’s perspective. This allows teams to focus on non-functional testing and other critical areas.
4. Efficient Cost Management: With proper resource planning, these tools can deliver a strong ROI, optimizing both time and budget.

Proof of Concept (POC) Observations

During our POC, we tested various use cases, including:

• Automating API calls.
• Fetching OTPs from mobile devices.
• Writing tests on one Android device and executing them across platforms without script-level changes.
• Writing test cases on instagram browsers

These functionalities demonstrated the potential of GenAI tools to simplify complex workflows and enhance efficiency.

Conclusion

GenAI tools hold immense promise for UI automation, offering solutions to longstanding challenges while enabling faster, more efficient testing cycles. They allow QA teams to adapt to tighter schedules and limited bandwidth without compromising quality.

In future articles, I’ll delve deeper into specific use cases and share detailed observations. Let’s continue the conversation on how GenAI tools can empower SDET/QA engineers to achieve their goals with greater ease and efficiency.