AI-Driven Test Automation Framework
Replaced a legacy automation framework with a modern Playwright and Appium-based solution featuring AI-powered self-healing, reducing test runtime by 80% and catching critical defects before production.
The Challenge
The existing test automation relied on a legacy, bloated framework producing flaky tests that were triggered manually through Jenkins jobs. Confidence in the test suite had eroded, and the maintenance overhead was unsustainable. This effort ran in parallel with a broader platform modernization — migrating web applications from ASP.NET and AngularJS to a React and Node.js stack, and transitioning native mobile apps from Objective-C to SwiftUI — which meant the automation framework had to be built to target rapidly evolving codebases from day one.
The Approach
- Designed and implemented a new end-to-end automation framework using Playwright for web applications and Appium with WebdriverIO for native iOS and Android apps
- Integrated AI-powered failure analysis to detect flaky versus genuine failures and implemented self-healing mechanisms into test workflows to automatically adapt to non-breaking UI changes
- Embedded automation as a first-class gate in critical UI repositories — tests run automatically on pull requests, merges, and release deployments via GitHub Actions
- Leveraged a hybrid execution infrastructure combining BrowserStack for cross-browser and device coverage, GitHub-hosted agents for CI pipelines, and a locally hosted VM farm for high-throughput parallel runs
The Outcome
Delivered stable end-to-end test suites covering critical user paths validated through production analytics data. Reduced overall test execution runtime by 80%. The primary ROI was a significant increase in pre-production bug identification, preventing interaction and subscription-related defects from reaching production and protecting revenue-critical user flows.