iSQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 CT-GenAI Question # 10 Topic 2 Discussion
CT-GenAI Exam Topic 2 Question 10 Discussion:
Question #: 10
Topic #: 2
You are using an LLM to assist in analyzing test execution trends to predict potential risks. Which of the following improvements would BEST enhance the LLM's ability to predict risks and provide actionable alerts?
A.
Emphasize constraints that focus on deviations that could impact release timelines or quality gates.
B.
Expand the output format to include risk predictions with severity levels, recommended actions, and a timeline for team intervention based on trend analysis.
C.
Specify that the role is a test analyst with expertise in predictive analytics and risk management.
D.
Add an instruction to calculate statistical variance and highlight tests that deviate by more than 20% from baseline metrics.
The effectiveness of an LLM is heavily dependent on the specificity of itsOutput Format. While role definition (Option C) and technical instructions (Option D) are helpful, the most significant "value add" for a test lead is receiving information that is directlyactionable. By expanding the output format to include structuredrisk predictions, severity levels, and recommended actions(Option B), the tester is forcing the LLM to perform a deeper level of analysis. Instead of just "flagging trends," the model must now synthesize the data to determinewhya trend is a risk andwhatthe team should do about it. This aligns with the "Advanced Prompting" section of the CT-GenAI syllabus, which emphasizes using AI for decision support. A structured report that includes a "timeline for intervention" allows the human tester to quickly validate the AI's logic and make informed decisions, transforming the LLM from a simple data summarizer into a strategic predictive tool that actively supports the maintenance of release quality and schedule adherence.
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