AI Chatbots and LLM-Powered Testing Applications for Software Testing CT-GENAI Practice Questions (Page 3)

Questions 11–15

1. 11application · easy

   A small startup wants to introduce an AI chatbot to assist manual testers with exploratory testing sessions. The chatbot should suggest test ideas based on the feature being tested. Which benefit is most directly realized by this approach?

   • AIt guarantees complete test coverage of the feature.
   • BIt reduces the tester's cognitive load by providing diverse, on-demand ideas to explore.
   • CIt automates the execution of all exploratory test cases.
   • DIt replaces the need for experienced testers.
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2. 12application · medium

   A test manager wants to use an LLM-powered application to automatically generate test cases from user stories. The team values traceability and wants to ensure each generated test case can be linked back to a specific acceptance criterion. What is the most effective approach?

   • AProvide the LLM with the user story and ask it to list all possible test scenarios in a free-form response.
   • BAsk the LLM to generate test cases and then manually review them for quality before adding them to the test management tool.
   • CUse a prompt that instructs the LLM to output test cases in a structured format, each tagged with the ID of the acceptance criterion it verifies.
   • DUse the LLM to generate test cases and store them in a separate document from the user stories.
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4. 13application · medium

   A support team deploys an AI chatbot to help developers file bug reports. The chatbot asks questions and fills a template. After a month, the team notices the reports contain plausible-sounding but incorrect stack traces. What is the most likely cause?

   • AThe developers are not providing enough detail in their answers to the chatbot.
   • BThe chatbot's temperature setting is too low, making its responses repetitive.
   • CThe chatbot was not integrated with the issue tracking system's API.
   • DThe LLM is hallucinating technical details that were not in the conversation.
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5. 14application · medium

   A team uses an AI chatbot to help write defect reports. The chatbot asks the tester questions and drafts a report. The team notices the reports are often missing the 'Expected Result' field. What is the best way to improve the chatbot's performance?

   • AUse a different LLM that is known to be better at generating text.
   • BTell the testers to manually add the expected result after the chatbot generates the report.
   • CAdd a mandatory prompt step that asks the tester for the expected result before generating the report.
   • DRetrain the chatbot on a dataset of defect reports that include expected results.
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6. 15foundation · easy

   Which statement best describes the role of an AI chatbot in a software testing team?

   • AIt serves as a conversational assistant that helps testers with tasks such as querying test data and interpreting results.
   • BIt acts as a fully autonomous test manager that makes all testing decisions.
   • CIt replaces the need for test automation frameworks entirely.
   • DIt functions as a static repository that stores test cases without any interactive capability.
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