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ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:

1. An LLM prioritizes tests using likelihood X impact but ranks a trivial tooltip change above a payment failure.
What defect does this MOST LIKELY show?

A) Hallucination
B) No defect; this is acceptable
C) Reasoning error in risk calculation logic
D) Dataset bias toward UI features

2. You must use GenAI to perform test analysis on a payments module with finalized requirements: (1) generate test conditions, (2) prioritize by risk, (3) check coverage gaps. Which sequence best applies prompt chaining?

A) Generate prioritized conditions in one shot -> verify coverage
B) Prioritize requirements -> generate conditions -> review defects
C) Generate conditions -> prioritize by risk -> map to requirements to find gaps
D) Detect requirement defects -> generate conditions -> prioritize

3. Which of the following is NOT a valid form of LLM-driven test data generation?

A) Creating production database backups
B) Creating combinatorial data (e.g., pairwise)
C) Generating synthetic datasets
D) Setting boundary values

4. Which AI approach requires feature engineering and structured data preparation?

A) Deep Learning
B) Generative AI
C) Classical Machine Learning
D) Symbolic AI

5. Which factor MOST influences the overall energy consumption of a Generative AI model used in software testing tasks?

A) The type of cloud platform affects processing speed but not total energy draw
B) The number of tokens processed directly determines the carbon intensity of each query
C) The location of the data center determines model bias and accuracy levels
D) The duration of user sessions primarily affects latency but not power efficiency

Solutions: