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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: Application of GenAI in Software Testing | - Practical use in testing workflows
|
| Topic 3: Organizational Adoption and Governance | - Enterprise GenAI adoption
|
| Topic 4: Prompt Engineering for Testing | - Prompt design techniques
|
| Topic 5: Risk, Quality, and Limitations of GenAI | - Risks in GenAI usage
|
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
Which AI approach requires feature engineering and structured data preparation?
- A. Deep Learning
- B. Symbolic AI
- C. Generative AI
- D. Classical Machine Learning
Correct Answer: D 🗳️
Explanation: Only visible for ValidVCE members. You can sign-up / login (it's free).
Who typically defines the system prompt in a testing workflow?
- A. Product owner in user stories only
- B. CI server automatically without human input
- C. End user during normal chat use
- D. A tester configuring the assistant
Correct Answer: D 🗳️
Explanation: Only visible for ValidVCE members. You can sign-up / login (it's free).
Which concept refers to breaking text into smaller units for processing by LLMs?
- A. Tokenization
- B. Context Window
- C. Transformer
- D. Embeddings
Correct Answer: A 🗳️
Explanation: Only visible for ValidVCE members. You can sign-up / login (it's free).
You must use GenAI to perform test analysis on a payments module with finalized requirements: (1) generate test conditions, (2) prioritize by risk, (3) check coverage gaps. Which sequence best applies prompt chaining?
- A. Generate prioritized conditions in one shot -> verify coverage
- B. Detect requirement defects -> generate conditions -> prioritize
- C. Generate conditions -> prioritize by risk -> map to requirements to find gaps
- D. Prioritize requirements -> generate conditions -> review defects
Correct Answer: C 🗳️
Explanation: Only visible for ValidVCE members. You can sign-up / login (it's free).
A team notices vague, inconsistent LLM outputs for the same story for two different prompts. Which technique BEST helps choose the stronger wording among two prompt versions using predefined metrics?
- A. A/B testing of prompts
- B. Integrating user feedback
- C. Output analysis
- D. Iterative prompt modification
Correct Answer: A 🗳️
Explanation: Only visible for ValidVCE members. You can sign-up / login (it's free).
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