Free ISTQB CT-GenAI Exam Questions

Become ISTQB Certified with updated CT-GenAI exam questions and correct answers

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Total 224 Questions | Updated On: Sep 22, 2026

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Question 1

Which option BEST differentiates the three prompting techniques?

A : Few-shot = no examples; Chaining = single prompt; Meta = disable iteration

B : Meta = step decomposition; Chaining = zero-shot only; Few-shot = manual optimization

C : Chaining = give examples; Few-shot = break tasks; Meta = manual edits only

D : Few-shot = examples; Chaining = multi-step prompts; Meta = model helps draft/refine prompts

Answer: D

Question 2

4.1.1 Which statement best describes why the architecture goes beyond a traditional client-server model?

A : It uses only in-house LLMs without external integration.

B : It replaces the server with multiple chatbots for redundancy.

C : It incorporates intelligent processing components like LLMs and multi-source back ends.

D : It eliminates the need for front-end and back-end separation.

Answer: C

Question 3

2.2.2 A Gherkin generation process produces correct syntax but omits edge case conditions. The tester adds example cases to the prompt before retrying. Which technique is this?

A : Zero-shot prompting

B : Meta prompting

C : Few-shot prompting

D : Multimodal prompting

Answer: C

Question 4

3.1.3 A team formats the test data fed into an LLM in CSV with clearly labeled columns instead of using a loosely formatted text file. Which risk reduction method is being used?

A : Select the appropriate GenAI model

B : Provide complete context

C : Compare results across models

D : Use clear, interpretable data formats

Answer: D

Question 5

1.1.4 A test engineer needs to identify mismatches between the expected UI layout described in user stories and screenshots from the latest build. They want to maximize test coverage by also generating additional test cases using the same model. Which approach is most suitable?

A : Use a multimodal LLM with a vision-language module

B : Use a reasoning LLM with chain-of-thought enabled

C : Use separate models for text and images, then combine results manually

D : Use a standard transformer trained only on text data

Answer: A

Page: 1 / 45

Total 224 Questions | Updated On: Sep 22, 2026

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