Locker’s failures are a significant problem for automation tests. A small change of UI, such as a renamed button and also an updated attribute or a new hierarchy of elements, can cause the broken scripts to break, so that it leads to the lost hours of purification, more decidrated constructions and even slower release cycles.

Lambdatest introduces Smart Heal to solve automation tests on real devices. Ai/ml algorithms give power to this new function. Smart Heal automatically detects, analyzes and recovers from locator failures during running time, ensuring that automation scripts remain quite resistant, even when the user interface changes.

Challenges before smart healing

Before Smart Heal, the failures of the locator were a recurring problem for the teams of Qa and Dev:

• Trenched tests: It even changes the small user interface how to change the name of a button or change an item that broke the scripts, causing frequent failures.
• Maintenance that requires time: The testers spent hours updating and fixing the locators manually after each launch.
• Pipe instability: CI/CD creations have often failed due to the problems of the locator, creating false negatives and slowing down deployments.
• Reloading Reliefs: The teams had to stop or divert the pipes only to tackle the discharge of tests, increasing the launch deadlines.
• Bad visibility: When a locator failed, there was no automated context or suggestions, the purification meant excavating through the line line by line.

Key benefits of Native Smart Cure for Automation Tests on Real Devices

• Automation of resistant evidence: It maintains stable automation by means of failure of the automatic healing locator during execution time, even when applications are subject to the frequent interest interface or domestic.
• Fastest shipping: Avoid testing of tests in fast launch cycles, allowing the market faster without compromising quality.
• Reduced maintenance effort: It minimizes the time that the teams spend manually broken scripts, allowing them to focus on expanding their testing coverage.
• Improvement of CI/CD reliability: It ensures the smoother pipe executions by automatically manipulating the troubles of decisive locators, reducing false negatives.
• Transparent healing records: Provides complete visibility with detailed records, cured lockers and screenshots before and after the board.
• Native debugging: It offers smart suggestions when healing is not possible, helping the testers to reinforce locators proactively.
• Real device accuracy: The healing occurs in the cloud of real Lambdatest devices, ensuring that the solutions are validated in environments that coincide with the conditions of the end user.
• Continuing reference updates: It maintains the basic lines of fresh locators learning from each race successfully, making the healing mechanism smarter over time.

How smart healing works

1. Base creation

Smart Heal requires at least one success test as a reference line. During this race, all element locators are captured and stored. This reference line acts as a basis for future healing attempts.

Tip: Ensure -You’s that your project and test names are consisting of executions for the reference application.

2. Base update

After each execution successfully, Smart Heal updates the reference line with the most recent creation that was completely passed, maintaining -aligned with the last status of the user interface.

3. Detection and healing

If you lack an element in the subsequent runs, Smart Heal remains AI to analyze the attributes, the domestic hierarchy and the visual evidence to find the closest valid coincidence.

4. Return -to return with a cured locator

Once a coincidence has been found, the passage is automatically reunited with the cured locator, allowing the test flow to continue perfectly. Both the original and the cured locators are registered by transparency.

5. Fallback and suggestions

If Smart Heal cannot be safely cured, AI-based suggestions are recorded on the board to help you strengthen your locators.

Review cured tests on Lambdatest Control Board

• Curation action records: Access the detailed records shown by the original and cured locators, giving a complete visibility on what was fixed during the race.
• Screenshot before and after: Check the screen catches of the user interface before and after the cure of the locator, helping to understand how the healing process worked.
• Cured and not cured items: Filter and view smart cure tests. The cured elements stand out, while the non -cured failures are red.
• Native insights: When Smart Heal cannot safely cure a locator, it provides AI-based suggestions and views on the control board to help you improve your locators.
• Summary Summary: Pass the cure tests to see a summary of the healing actions taken during the session, making the purification faster and more efficient.

Access early

Smart Heal is currently in Beta Closed and quickly evolves with users’ feedback. If you want to try –

👉 Re -make our chat 24 × 7 or send us an email to [email protected].
👉 Once published publicly, Smart Heal will be included under AI credits.

Make your automation smarter, faster and more resistant to Lambdatest Smart Heal.