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

2. Which technique MOST directly reduces hallucinations by grounding the model in project realities?

A) Use longer temperature settings
B) Provide detailed context
C) Randomize prompts each run
D) Rely on generic examples only

3. In the context of software testing, which statements (i-v) about foundation, instruction-tuned, and reasoning LLMs are CORRECT?
i. Foundation LLMs are best suited for broad exploratory ideation when test requirements are underspecified.
ii. Instruction-tuned LLMs are strongest at adhering to fixed test case formats (e.g., Gherkin) from clear prompts.
iii. Reasoning LLMs are strongest at multi-step root-cause analysis across logs, defects, and requirements.
iv. Foundation LLMs are optimal for strict policy compliance and template conformance.
v. Instruction-tuned LLMs can follow stepwise reasoning without any additional training or prompting.

A) ii, iii, iv
B) i, ii, iii
C) i, ii, iii (Duplicate entry in original source)
D) i, iii, v

4. Who typically defines the system prompt in a testing workflow?

A) A tester configuring the assistant
B) CI server automatically without human input
C) End user during normal chat use
D) Product owner in user stories only

5. Which statement about data privacy risks in GenAI-assisted testing is INCORRECT?

A) GenAI outputs can accidentally reveal sensitive information present in inputs
B) Some GenAI tools may store/process data without explicit consent
C) Strict GDPR compliance eliminates all privacy risk
D) Using GenAI without regulatory compliance can lead to legal exposure

Solutions: