Use AI to Double Your Test Suite for a Higher ROI

Does your web UI testing achieve the repeatable and maintainable test automation that you need to validate the application’s functionality efficiently?

As applications become more complex with underlying microservices and integrated architectures, testing strategies need to adjust to a Lean UI approach and incorporate API testing to test the application’s functionality more efficiently and thoroughly. Combining this with AI-powered test automation, QA teams can easily and rapidly double their test suites and boost testing ROI.

Watch this session to learn about:

• Why organizations are adopting Lean UI testing principles to scale regression testing.
• How to increase testing ROI by expanding beyond web UI testing.
• How to leverage AI to quickly create API test suites from existing web UI tests.

The Limitations of Web UI Testing

While web UI testing has its place for validating user experience and cross-browser compatibility, it comes with several drawbacks:

• Flakiness and Maintenance: UI tests are notoriously unstable and difficult to maintain, especially with frequent UI changes during early development. This leads to a high maintenance burden on teams.
• Slow Execution: Browsers are resource-intensive, and UI actions are sequential. This means tests take a long time to run, impacting feedback loops to development.
• Difficult Root Cause Analysis: Diagnosing failures in UI tests is complex. It’s hard to pinpoint if the issue lies in the front-end code, backend APIs, or elsewhere.
• Increasing Complexity: Modern applications with microservices and complex architectures require more complex UI tests, demanding more time for setup and ongoing maintenance, hindering scalability.

These limitations directly impact key drivers for test automation: speed, quality, risk reduction, and cost.

The Rise of API Testing and the Testing Pyramid

As applications evolve with microservices and experience APIs (the APIs your UIs are built upon), testing strategies must adapt. The concept of a lean UI testing approach emphasizes API testing for functional validation, aligning with the testing pyramid.

The testing pyramid suggests a foundation of unit and API tests, which are more efficient, easier to automate, and faster for diagnosing failures. UI and manual tests, while valuable, should be used more judiciously.

However, many teams find themselves with an “ice cream cone” or “goblet” shape, meaning more UI tests than API or unit tests. This is where API testing, particularly for experience APIs, offers a significant opportunity.

Key Takeaways:

• Increased Efficiency: API tests are more resilient to change than UI tests, reducing maintenance hours and stabilizing automation.
• Faster Feedback: API tests run much faster than UI tests, accelerating regression testing and providing quicker feedback to development teams.
• Easier Diagnostics: Failures in API tests are easier to diagnose compared to UI tests.
• Reduced Costs: Earlier feedback and faster remediation reduce the cost of fixing defects.
• Scalability: Shifting to API testing allows test automation to scale more easily without the typical maintenance burdens of UI testing.

Transforming UI Tests into API Tests with AI

Misconceptions about API testing, such as its difficulty or unclear ownership, can be a barrier. This is where AI and machine learning come into play.

Parasoft’s solutions can automatically convert existing web UI tests into API scenario tests, regardless of the framework used (like Selenium, Cypress, or Playwright). This is achieved by capturing network traffic during UI test execution and using AI to build a model of stateful data, parameterizing it to faithfully execute the business logic defined by the UI flow.

How it Works:

1. Record UI Tests: Execute your existing web UI tests.
2. Capture Network Traffic: The system records the API calls made by the UI.
3. AI Analysis: AI analyzes the traffic to identify and parameterize dynamic data (like order numbers) and suggest assertions based on observed data changes.
4. Generate API Tests: The AI generates API tests that replicate the functionality of the UI tests but run at the API layer.

This process allows QA teams to rapidly double their test suites by reusing their existing UI test investments.

Benefits of AI-Generated API Tests:

• Speed: Tests run significantly faster (e.g., 33 seconds for UI vs. 1 second for API).
• Stability: API tests are less prone to breaking from UI changes.
• Maintainability: Lower maintenance effort compared to UI tests.
• Data-Driven Testing: Easily loop through different data conditions for comprehensive testing.
• Shift-Left Security & Performance: Re-use functional API tests for penetration, load, and performance testing early in the development cycle.

Conclusion

While UI testing remains valuable, relying solely on it for functional validation in modern, complex applications is not sustainable. By adopting a lean UI testing strategy and shifting focus to API testing, especially for experience APIs, organizations can achieve a more scalable, maintainable, and efficient test automation strategy. AI-powered solutions make this transition accessible, enabling teams to double their test suites, improve quality, reduce costs, and accelerate delivery.

API testing, including experience APIs, offers a higher ROI than UI testing alone. It provides a scalable and maintainable approach, ensuring quality and increasing testing thoroughness. For teams heavily invested in web UI testing, AI offers a straightforward path to reuse existing scripts and create complementary API scenario tests, maximizing test strategy ROI.