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iSQI CT-GenAI Exam Questions

iSQI CT-GenAI Exam Questions Answers

ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0

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iSQI CT-GenAI Practice Test Questions ( Updated) – Real Exam Questions & Dumps PDF

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iSQI CT-GenAI Sample Questions – Free Practice Test & Real Exam Prep

Question #1

Which technique MOST directly reduces hallucinations by grounding the model in project realities? 

  • A. Provide detailed context 
  • B. Randomize prompts each run 
  • C. Rely on generic examples only 
  • D. Use longer temperature settings 
Answer: A 
Question #2

Which statement BEST differentiates an LLM-powered test infrastructure from a traditional chatbot system used in testing? 

  • A. It dynamically generates test insights using contextual information 
  • B. It produces scripted conversational responses similar to traditional bots 
  • C. It focuses primarily on visual dashboards and user navigation features 
  • D. It provides fixed responses from predefined rule sets and scripts 
Answer: A 
Question #3

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

  • A. Select models with maximum vendor visibility and strong online presence to ensure reliability 
  • B. Select open-source models prioritizing creativity over compliance or performance consistency 
  • C. Select broad-coverage models offering diverse functionalities for various test scenarios 
  • D. Select LLMs aligned to measurable test outcomes, compatible with current infrastructure 
Answer: D 
Question #4

What defines a prompt pattern in the context of structured GenAI capability building? 

  • A. Treating prompts as access credentials or compliance records rather than functional templates
  • B. Maintaining static documentation repositories without real-time prompt standardization processes
  • C. Applying a reusable and structured template that guides GenAI models toward consistent outputs
  • D. Using ad hoc prompts without reference to previously proven structures or examples 
Answer: C 
Question #5

What does an embedding represent in an LLM? 

  • A. Tokens grouped into context windows 
  • B. Numerical vectors capturing semantic relationships 
  • C. Logical rules for reasoning 
  • D. A set of test cases for validation 
Answer: B 
Question #6

What distinguishes an LLM-powered agent from a basic AI chatbot in test processes? 

  • A. Reliance on predefined templates to generate short, factual answers 
  • B. Ability to respond to prompts without explicit user instructions 
  • C. Ability to trigger automated actions beyond conversation 
  • D. Use of a conversational tone and improved response personalization 
Answer: C 
Question #7

A team notices vague, inconsistent LLM outputs for the same story for two differentprompts. Which technique BEST helps choose the stronger wording among two promptversions using predefined metrics?

  • A. A/B testing of prompts 
  • B. Iterative prompt modification 
  • C. Output analysis 
  • D. Integrating user feedback 
Answer: A 
Question #8

When an organization uses an AI chatbot for testing, what is the PRIMARY LLMOps concern? 

  • A. Maximizing scalability by deploying larger cloud-based LLM clusters 
  • B. Maintaining data privacy and minimizing security risks from external services 
  • C. Achieving faster responses by reducing model checkpoints and updates 
  • D. Focusing primarily on user experience improvements and response formatting 
Answer: B 
Question #9

You are tasked with applying structured prompting to perform impact analysis on recentcode changes. Which of the following improvements would BEST align the prompt withstructured prompt engineering best practices for comprehensive impact analysis?

  • A. Include references to version control systems like Git in the constraints. 
  • B. Specify that the role is a test architect specializing in CI/CD pipelines. 
  • C. Add a step to review the change log for syntax errors before analysis. 
  • D. Include mapping code changes to affected modules, identifying test cases, prioritizing by risk level and change complexity
Answer: D 
Question #10

You are using an LLM to assist in analyzing test execution trends to predict potential risks.Which of the following improvements would BEST enhance the LLM's ability to predict risksand provide actionable alerts?

  • A. Emphasize constraints that focus on deviations that could impact release timelines or quality gates.
  • B. Expand the output format to include risk predictions with severity levels, recommended actions, and a timeline for team intervention based on trend analysis.
  • C. Specify that the role is a test analyst with expertise in predictive analytics and risk management.
  • D. Add an instruction to calculate statistical variance and highlight tests that deviate by more than 20% from baseline metrics.
Answer: B 
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