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

1. Which option BEST differentiates the three prompting techniques?

A) Few-shot = no examples; Chaining = single prompt; Meta = disable iteration
B) Few-shot = examples; Chaining = multi-step prompts; Meta = model helps draft/refine prompts
C) Chaining = give examples; Few-shot = break tasks; Meta = manual edits only
D) Meta = step decomposition; Chaining = zero-shot only; Few-shot = manual optimization

2. What is a hallucination in LLM outputs?

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

3. What defines a prompt pattern in the context of structured GenAI capability building?

A) Using ad hoc prompts without reference to previously proven structures or examples
B) Applying a reusable and structured template that guides GenAI models toward consistent outputs
C) Treating prompts as access credentials or compliance records rather than functional templates
D) Maintaining static documentation repositories without real-time prompt standardization processes

4. Which setting can reduce variability by narrowing the sampling distribution during inference?

A) Using a larger context window
B) Increasing temperature
C) Lowering temperature
D) Increasing learning rate

5. A tester uploads crafted images that steer the LLM into validating non-existent acceptance criteria. Which attack vector is this?

A) Malicious code generation
B) Request manipulation
C) Data poisoning
D) Data exfiltration

Solutions: