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ISQI CT-GenAI Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Foundations of Generative AI and LLMs | - Introduction to Generative AI in Software Testing
|
| Topic 2: Risk, Quality, and Limitations of GenAI | - Risks in GenAI usage
|
| Topic 3: Prompt Engineering for Testing | - Prompt design techniques
|
| Topic 4: Application of GenAI in Software Testing | - Practical use in testing workflows
|
| Topic 5: Organizational Adoption and Governance | - Enterprise GenAI adoption
|
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
What does an embedding represent in an LLM?
- A. Logical rules for reasoning
- B. Numerical vectors capturing semantic relationships
- C. A set of test cases for validation
- D. Tokens grouped into context windows
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Which statement BEST contrasts interaction style and scope?
- A. Chatbots enable conversational interactions; LLM apps provide capabilities for defined test tasks.
- B. Both are identical aside from UI theme.
- C. Chatbots enforce fixed workflows; LLM apps support free-form exploration beneficial for software testing
- D. Chatbots require API integration; LLM apps do not.
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Which statement about data privacy risks in GenAI-assisted testing is INCORRECT?
- A. Strict GDPR compliance eliminates all privacy risk
- B. Some GenAI tools may store/process data without explicit consent
- C. Using GenAI without regulatory compliance can lead to legal exposure
- D. GenAI outputs can accidentally reveal sensitive information present in inputs
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An attacker sends extremely long prompts to overflow context so the model leaks snippets from its training data. Which attack vector is this?
- A. Data poisoning
- B. Malicious code generation
- C. Request manipulation
- D. Data exfiltration
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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. No defect; this is acceptable
- B. Reasoning error in risk calculation logic
- C. Hallucination
- D. Dataset bias toward UI features
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