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

1. Which competency MOST helps testers steer LLMs to produce useful, on-policy testware?

A) Designing custom CPU instructions
B) Mastering prompt engineering
C) Configuring network routers
D) Writing low-level device drivers

2. A team notices vague, inconsistent LLM outputs for the same story for two different prompts. Which technique BEST helps choose the stronger wording among two prompt versions using predefined metrics?

A) A/B testing of prompts
B) Iterative prompt modification
C) Integrating user feedback
D) Output analysis

3. When an organization uses an AI chatbot for testing, what is the PRIMARY LLMOps concern?

A) Maintaining data privacy and minimizing security risks from external services
B) Achieving faster responses by reducing model checkpoints and updates
C) Focusing primarily on user experience improvements and response formatting
D) Maximizing scalability by deploying larger cloud-based LLM clusters

4. What is a hallucination in LLM outputs?

A) A systematic preference learned from data
B) A transient network failure during inference
C) A logical mistake in multi-step deduction
D) Generation of factually incorrect content for the task

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

Solutions: