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Are you curious about CT-GenAI exam dumps? Do you want to have a better understanding of CT-GenAI exam training material? Please pay attention to the following.
| Section | Weight | Objectives |
|---|---|---|
| Deploying and Integrating GenAI in Test Organisations | 15% | - Measuring value and continuous improvement - Strategy, governance, and adoption roadmap - Roles, skills, and team readiness |
| Prompt Engineering for Effective Software Testing | 35% | - Prompt patterns for test design, data generation, automation - Iterative refinement and evaluation of prompts - Principles and structure of effective prompts |
| LLM-Powered Test Infrastructure | 10% | - RAG, fine-tuning, and model adaptation - AI agents and integration with test tools - Architecture and deployment considerations |
| Introduction to Generative AI for Software Testing | 15% | - Core concepts: Generative AI, LLMs, foundation models - Use cases across the testing lifecycle - Capabilities and limitations relevant to testing |
| Managing Risks of Generative AI in Software Testing | 25% | - Hallucinations, bias, inaccuracy, and consistency risks - Validation, verification, and mitigation strategies - Data privacy, security, and compliance concerns |
1. You are tasked with applying structured prompting to perform impact analysis on recent code changes. Which of the following improvements would BEST align the prompt with structured prompt engineering best practices for comprehensive impact analysis?
A) Specify that the role is a test architect specializing in CI/CD pipelines.
B) Include references to version control systems like Git in the constraints.
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
2. An LLM prioritizes tests using likelihood X impact but ranks a trivial tooltip change above a payment failure.
What defect does this MOST LIKELY show?
A) Reasoning error in risk calculation logic
B) Hallucination
C) Dataset bias toward UI features
D) No defect; this is acceptable
3. Which standard specifies requirements for managing AI systems within an organization, supporting consistent GenAI use in testing?
A) ISO/IEC 23053:2022
B) NIST AI RMF 1.0
C) ISO/IEC 42001:2023
D) EU AI Act
4. What does an embedding represent in an LLM?
A) A set of test cases for validation
B) Logical rules for reasoning
C) Numerical vectors capturing semantic relationships
D) Tokens grouped into context windows
5. Which option BEST differentiates the three prompting techniques?
A) Few-shot = no examples; Chaining = single prompt; Meta = disable iteration
B) Chaining = give examples; Few-shot = break tasks; Meta = manual edits only
C) Meta = step decomposition; Chaining = zero-shot only; Few-shot = manual optimization
D) Few-shot = examples; Chaining = multi-step prompts; Meta = model helps draft/refine prompts
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: D |
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