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

ISQI CT-GenAI exam
  • Exam Code: CT-GenAI
  • Exam Name: ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0
  • Updated: Aug 17, 2026
  • Q & A: 42 Questions and Answers
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ISQI CT-GenAI Exam Syllabus Topics:
SectionWeightObjectives
Topic 1: Fundamentals of Generative AI20%- Generative AI Concepts
  • 1. Emergent capabilities and limitations
  • 2. Model types (Base, Instruction-tuned, RAG)
  • 3. AI model behavior
  • 4. Training data and context windows
  • 5. Hallucinations
  • 6. Alignment and guardrails
- AI Development Lifecycle
  • 1. Deployment and monitoring
  • 2. Evaluation
  • 3. Model training and fine-tuning
  • 4. Data collection, preparation, and curation
- AI Terminology
  • 1. Deep Learning
  • 2. Transformer architecture
  • 3. Tokens and prompts
  • 4. Machine Learning (ML)
  • 5. Generative AI (GenAI)
  • 6. Artificial Intelligence (AI)
  • 7. Large Language Models (LLMs)
Topic 2: Tools for Testing Generative AI20%- Using Tools for Common Testing Activities
  • 1. Simulation and monitoring tools
  • 2. Model evaluation tools
  • 3. Prompt testing tools
  • 4. Security testing tools
- Testing Tools Overview
  • 1. Categories of GenAI testing tools
  • 2. Selecting appropriate tools for specific testing needs
Topic 3: Risks and Testing Challenges for Generative AI30%- Testing Challenges for Generative AI
  • 1. Subjectivity of quality assessment
  • 2. Non-deterministic output behavior
  • 3. Ethical testing concerns
  • 4. Complexity of the AI component
  • 5. Coverage challenges
  • 6. Test oracle problem
  • 7. Regulatory and compliance considerations
- Quality Risks Specific to Generative AI
  • 1. Inconsistent responses across runs
  • 2. Inappropriate output for the context
  • 3. Input sensitivity (prompt brittleness)
  • 4. Dependency on external components
  • 5. Incorrect or fabricated outputs (hallucinations)
  • 6. Offensive, harmful, or biased content
Topic 4: Testing Activities for Generative AI30%- Model and Output Evaluation
  • 1. Human evaluation methods
  • 2. Metamorphic testing
  • 3. Automated evaluation methods
  • 4. Output correctness and quality assessment
  • 5. Checkpoint testing
- Prompt-Based Testing
  • 1. Prompt engineering basics
  • 2. Test case design using prompts
  • 3. Test data creation with GenAI
- Traceability and Documentation
  • 1. Documentation requirements for AI testing
  • 2. Test coverage of AI model components
- Requirements-Based Testing
  • 1. Functional requirements for AI-based systems
  • 2. Non-functional requirements for AI-based systems
  • 3. AI-related quality requirements
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:

1. Which concept refers to breaking text into smaller units for processing by LLMs?

A) Context Window
B) Tokenization
C) Embeddings
D) Transformer


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

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


3. What does an embedding represent in an LLM?

A) Numerical vectors capturing semantic relationships
B) Logical rules for reasoning
C) Tokens grouped into context windows
D) A set of test cases for validation


4. Which option BEST differentiates the three prompting techniques?

A) Few-shot = examples; Chaining = multi-step prompts; Meta = model helps draft/refine prompts
B) Chaining = give examples; Few-shot = break tasks; Meta = manual edits only
C) Few-shot = no examples; Chaining = single prompt; Meta = disable iteration
D) Meta = step decomposition; Chaining = zero-shot only; Few-shot = manual optimization


5. 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) Generate conditions -> prioritize by risk -> map to requirements to find gaps
C) Prioritize requirements -> generate conditions -> review defects
D) Detect requirement defects -> generate conditions -> prioritize


Solutions:

Question # 1
Answer: B
Question # 2
Answer: A
Question # 3
Answer: A
Question # 4
Answer: A
Question # 5
Answer: B

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