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You have been developing test automation for an e-commerce system. One of the problems you are seeing is that object recognition in the GUI is having frequent failures. You have determined this is because the developers are changing the identifiers when they make code updates. How could AI help make the automation more reliable?
Correct Answer: A
Object recognition issues in test automation often arise whendevelopers frequently change object identifiers in the GUI. AI can enhance the stability of GUI automation by: * Using multiple criteria for object identification * AI cantrack UI elements using multiple attributessuch asXPath, label, ID, class, and screen coordinatesrather than relying on a single identifier that may change over time. * This approach makes the automationless brittle and more adaptive to changes in the UI. * Why other options are incorrect? * B (Ignore unrecognizable objects to avoid failures): Ignoring objects instead of identifying them properly wouldlead to incomplete or incorrect test execution. * C (Dynamically name objects and alter source code): AI-based testing tools donot modify application source code; they work byadjusting the recognition strategy. * D (Anticipate developer changes and pre-alter automation code): While AI can adapt,it does not predict future changes to the GUI, making this option unrealistic. Thus,Option A is the best answer, as AI tools enhance object recognitionby dynamically selecting the most stable and persistent identification methods, improving test automation reliability. Certified Tester AI Testing Study Guide References: * ISTQB CT-AI Syllabus v1.0, Section 11.6.1 (Using AI to Test Through the Graphical User Interface (GUI)) * ISTQB CT-AI Syllabus v1.0, Section 11.6.2 (Using AI to Test the GUI).
