Question 1

3.4.1 A QA lead is tasked with ensuring that their GenAI testing pipeline follows best practices for data quality, transparency, and fault tolerance. Which standard directly addresses these needs?

Options :

A : NIST AI Risk Management Framework

B : ISO/IEC 42001:2023

C : ISO/IEC 23053:2022

D : EU AI Act

Answer: C

Question 2

4.1.1 In the architecture of an LLM-powered test infrastructure, which component manages authentication, data retrieval, and prompt preparation?

Options :

A : Front-end

B : Back-end

C : LLM model

D : External data sources

Answer: B

Question 3

2.2.1 A tester provides an LLM with regulatory compliance requirements, historical defect data, and business rules. Which GenAI-supported test analysis task is most directly enabled by this combination?

Options :

A : Identifying ambiguities in GUI layouts

B : Generating non-prioritized test conditions

C : Prioritizing test conditions based on risk level

D : Suggesting test techniques based solely on text patterns

Answer: C

Question 4

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

Options :

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 5

1.1.4 A software testing team needs to evaluate whether a multimodal LLM can handle both textual defect reports and related application screenshots in a single test prompt. What is the key preprocessing step for the image before passing it to the transformer architecture?

Options :

A : Convert it into text via OCR

B : Convert it into embeddings using a vision-language model

C : Directly feed the raw pixel data to the transformer

D : Compress it into a binary format

Answer: B

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