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ISQI CT-GenAI Exam Syllabus Topics:

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

2. Which option BEST differentiates the three prompting techniques?

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

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

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

4. What is a hallucination in LLM outputs?

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

5. You must generate test cases for a new payments rule. The system includes API specifications stored in a vector database and prior tests in a relational database. Which of the following sequences BEST represents the correct order for applying a Retrieval-Augmented Generation (RAG) workflow?
i. Retrieve semantically similar specification chunks from the vector database ii. Feed both retrieved datasets as context for the LLM to generate new test cases iii. Retrieve relevant historical cases from the relational database iv. Submit a focused query describing the new test requirement

A) iii -> iv -> i -> ii
B) iv -> iii -> i -> ii
C) i -> iv -> iii -> ii
D) iv -> i -> iii -> ii

Solutions: