Question 1

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 2

1.2.2 A tester is new to the team and needs quick clarifications on exploratory test approaches for a mobile banking app. They want answers immediately, without setting up any additional tools. What is the most efficient approach?

Options :

A : Integrate LLM API into the existing test management system for automated responses

B : Use an AI chatbot with prompt chaining for quick, conversational guidance

C : Build a custom LLM-powered tool for exploratory testing automation

D : Write manual documentation for exploratory testing steps

Answer: B

Question 3

4.2.1 During fine-tuning of an LLM for test generation, the training dataset contains inconsistencies: some user stories are incomplete, and some test cases do not match the described functionality. After fine-tuning, the model frequently generates irrelevant or biased test cases. Which fine-tuning challenge does this illustrate?

Options :

A : Overfitting caused by small dataset size.

B : Opacity in the model’s reasoning.

C : Computational overhead in processing large models.

D : Poor training data quality.

Answer: D

Question 4

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?

Options :

A : Zero-shot prompting

B : Meta prompting

C : Few-shot prompting

D : Multimodal prompting

Answer: C

Question 5

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

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