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

1. Which concept refers to breaking text into smaller units for processing by LLMs?

A) Context Window
B) Tokenization
C) Embeddings
D) Transformer

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

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

3. What does an embedding represent in an LLM?

A) Numerical vectors capturing semantic relationships
B) Logical rules for reasoning
C) Tokens grouped into context windows
D) A set of test cases for validation

4. Which option BEST differentiates the three prompting techniques?

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

5. 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) Generate conditions -> prioritize by risk -> map to requirements to find gaps
C) Prioritize requirements -> generate conditions -> review defects
D) Detect requirement defects -> generate conditions -> prioritize

Solutions: