Introducing AI-Native Smart Heal for Automation Tests on Real Devices

Locator failures are a meaningful problem for automation tests. A small UI change such as a renamed button and also an updated attribute or a new element hierarchy can cause brittle scripts to break so it leads to wasted debugging hours plus flaky builds and even slower release cycles.

LambdaTest introduces Smart Heal to solve this for Automation Tests on Real Devices. AI/ML algorithms give power to this new feature. Smart Heal automatically detects, analyzes as well as recovers from locator failures during runtime, ensuring your automation scripts stay quite resilient, even when the UI changes.

Challenges Before Smart Heal

Before Smart Heal, locator failures were a recurring problem for QA and Dev teams:

• Brittle Tests: Even small UI changes like renaming a button or shifting an element broke scripts, causing frequent failures.
• Time-Consuming Maintenance: Testers spent hours updating and fixing locators manually after every release.
• Pipeline Instability: CI/CD builds often failed due to locator issues, creating false negatives and slowing deployments.
• Delayed Releases: Teams had to halt or rerun pipelines just to address test flakiness, increasing release timelines.
• Poor Visibility: When a locator failed, there was no automated context or suggestions, debugging meant digging through logs line by line.

Key Benefits of AI-Native Smart Heal for Automation Tests on Real Devices

• Resilient Test Automation: Keeps automation stable by auto-healing locator failures during runtime, even when apps undergo frequent UI or DOM changes.
• Faster Shipments: Prevents test breakages in fast-moving release cycles, enabling quicker go-to-market without compromising quality.
• Reduced Maintenance Effort: Minimizes the time teams spend fixing broken scripts manually, letting them focus on expanding test coverage instead.
• Improved CI/CD Reliability: Ensures smoother pipeline executions by automatically handling flaky locator issues, reducing false negatives.
• Transparent Healing Logs: Provides full visibility with detailed logs, healed locator mappings, and before-and-after screenshots in the dashboard.
• AI-Native Debugging: Delivers intelligent suggestions when healing isn’t possible, helping testers strengthen locators proactively.
• Real-Device Accuracy: Healing happens on LambdaTest’s real device cloud, ensuring fixes are validated in environments that match end-user conditions.
• Continuous Baseline Updates: Keeps locator baselines fresh by learning from every successful run, making the healing mechanism smarter over time.

How Smart Heal Works

1. Baseline Creation

Smart Heal requires at least one successful test run as a baseline. During this run, all element locators are captured and stored. This baseline acts as the foundation for future healing attempts.

Tip: Ensure your project and test names remain consistent across runs for baseline application.

2. Baseline Updation

After every successful run, Smart Heal updates the baseline with the most recent fully passed build, keeping it aligned with the latest UI state.

3. Detection and Healing

If an element is missing in subsequent runs, Smart Heal leverages AI to analyze attributes, DOM hierarchy, and visual cues to find the closest valid match.

4. Retry with Healed Locator

Once a match is found, the step retries automatically with the healed locator, allowing the test flow to continue seamlessly. Both original and healed locators are logged for transparency.

5. Fallback and Suggestions

If Smart Heal cannot confidently heal, AI-driven suggestions are recorded in the dashboard to help you strengthen your locators.

Note

Enable AI Smart Heal in Your Tests. Here is the detailed documentation.

Review Healed Tests in the LambdaTest Dashboard

• Healing Action Logs: Access detailed logs showing both the original and healed locators, giving you full visibility into what was fixed during the run.
• Before-and-After Screenshots: View side-by-side screenshots of the UI before and after the locator healing, helping you understand how the healing process worked.
• Healed and Unhealed Elements: Easily filter and view tests where Smart Heal was applied. Healed elements are highlighted, while unhealed failures are marked in red.
• AI-Native Insights: When Smart Heal can’t confidently heal a locator, it provides AI-driven suggestions and insights in the dashboard to help you improve your locators.
• Session Summaries: Hover over healed test builds to see a summary of the healing actions performed during the session, making debugging faster and more efficient.

Get Early Access

Smart Heal is currently in closed beta and evolving rapidly with user feedback. If you’d like to try it for your team:

👉 Reach out via our 24×7 chat or email us at support@lambdatest.com.
👉 Once publicly released, Smart Heal will be included under AI credits.

Make your automation smarter, faster, and more resilient with LambdaTest Smart Heal.

Bhawana

Bhawana is a Community Evangelist at LambdaTest with over two years of experience creating technically accurate, strategy-driven content in software testing. She has authored 20+ blogs on test automation, cross-browser testing, mobile testing, and real device testing. Bhawana is certified in KaneAI, Selenium, Appium, Playwright, and Cypress, reflecting her hands-on knowledge of modern automation practices. On LinkedIn, she is followed by 5,500+ QA engineers, testers, AI automation testers, and tech leaders.

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