Prepare and pass exam with our ISQI CT-GenAI training material, here you will achieve your dream easily With TrainingQuiz!
Updated: Aug 20, 2026
No. of Questions: 42 Questions & Answers with Testing Engine
Download Limit: Unlimited
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| Certification Vendor: | ISTQB® / iSQI (International Software Quality Institute) / Member Boards |
| Exam Name: | Certified Tester Testing with Generative AI (CT-GenAI) |
| Exam Number: | CT-GenAI v1.0 |
| Real Exam Qty: | 40 multiple-choice questions |
| Exam Format: | Multiple-choice, Single-answer questions, Scenario-based comprehension questions |
| Exam Price: | Varies by region (~230–260 EUR typical EU pricing; provider-dependent) |
| Certificate Validity Period: | No expiry for certification (ISTQB certifications are generally lifelong) |
| Passing Score: | Approximately 65% (typically 26/40 correct answers; varies slightly by board) |
| Exam Duration: | 60 (+15 min extension for non-native language candidates) |
| Related Certifications: | ISTQB Certified Tester Foundation Level (CTFL) |
| Available Languages: | English, Local language versions depending on member board |
| Recommended Training: | ISTQB CT-GenAI Syllabus (Official PDF) ISTQB Sample Exams & Resources |
| Exam Registration: | Member Board / Exam Providers (varies by country) ISTQB Official Certification Portal |
| Sample Questions: | ISQI CT-GenAI Sample Questions |
| Exam Way: | Online proctored or test center (Pearson VUE / ISTQB member boards depending on region) |
| Pre Condition: | ISTQB Certified Tester Foundation Level (CTFL) is required |
| Official Syllabus URL: | https://www.istqb.org/certifications/gen-ai/ |
| Section | Objectives |
|---|---|
| Foundations of Generative AI and LLMs | - Introduction to Generative AI in Software Testing
|
| Risk, Quality, and Limitations of GenAI | - Risks in GenAI usage
|
| Application of GenAI in Software Testing | - Practical use in testing workflows
|
| Organizational Adoption and Governance | - Enterprise GenAI adoption
|
| Prompt Engineering for Testing | - Prompt design techniques
|
1. What is a hallucination in LLM outputs?
A) Generation of factually incorrect content for the task
B) A systematic preference learned from data
C) A transient network failure during inference
D) A logical mistake in multi-step deduction
2. A prompt begins: "You are a senior test manager responsible for risk-based test planning on a payments platform." Which component is this?
A) Role
B) Constraints
C) Context
D) Instruction
3. What is a key data-related aspect when defining a GenAI strategy for testing?
A) Aggregate data from all available organizational repositories without filtration
B) Use only auto-generated synthetic data to avoid dependency on enterprise repositories
C) Neglect legacy data sources as they provide limited immediate relevance to testing tasks
D) Prioritize accurate and relevant input data secured through defined quality procedures
4. Which option BEST differentiates the three prompting techniques?
A) Chaining = give examples; Few-shot = break tasks; Meta = manual edits only
B) Meta = step decomposition; Chaining = zero-shot only; Few-shot = manual optimization
C) Few-shot = examples; Chaining = multi-step prompts; Meta = model helps draft/refine prompts
D) Few-shot = no examples; Chaining = single prompt; Meta = disable iteration
5. Which consideration BEST aligns LLM choice with organizational goals in a GenAI testing strategy?
A) Select open-source models prioritizing creativity over compliance or performance consistency
B) Select LLMs aligned to measurable test outcomes, compatible with current infrastructure
C) Select models with maximum vendor visibility and strong online presence to ensure reliability
D) Select broad-coverage models offering diverse functionalities for various test scenarios
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: D | Question # 4 Answer: C | Question # 5 Answer: B |
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