ISQI CT-GenAI test insides dumps : ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0

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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. 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) Data poisoning
C) Data exfiltration
D) Request manipulation

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 consideration BEST aligns LLM choice with organizational goals in a GenAI testing strategy?

A) Select LLMs aligned to measurable test outcomes, compatible with current infrastructure
B) Select open-source models prioritizing creativity over compliance or performance consistency
C) Select models with maximum vendor visibility and strong online presence to ensure reliability
D) Select broad-coverage models offering diverse functionalities for various test scenarios

4. What are the three key phases in adopting GenAI in a test organization?

A) Prototype; pilot; decommission
B) Discovery; initiation and usage definition; utilization and iteration
C) Planning; execution; sign-off
D) Training; certification; outsourcing

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

Solutions: