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

  • Exam Code: CT-GenAI
  • Exam Name: ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0
  • Updated: Oct 07, 2026
  • Q & A: 42 Questions and Answers

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ISQI CT-GenAI Exam Syllabus Topics:

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

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

Question #1

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
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #2

Which of the following is NOT a valid form of LLM-driven test data generation?

  • A. Setting boundary values
  • B. Generating synthetic datasets
  • C. Creating combinatorial data (e.g., pairwise)
  • D. Creating production database backups
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #3

Which statement BEST contrasts interaction style and scope?

  • A. Chatbots enforce fixed workflows; LLM apps support free-form exploration beneficial for software testing
  • B. Chatbots enable conversational interactions; LLM apps provide capabilities for defined test tasks.
  • C. Both are identical aside from UI theme.
  • D. Chatbots require API integration; LLM apps do not.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #4

Consider applying the meta-prompting technique to generate automated test scripts for API testing. You need to test a REST API endpoint that processes user registration with validation rules. Which one of the following prompts is BEST suited to this task?

  • A. Role: Act as a test automation engineer. | Context: You are creating tests for a registration endpoint. | Instruction: Generate Python test scripts using pytest covering both valid and invalid inputs. | Input Data: POST /api/register with email and password. | Constraints: Follow pytest structure. | Output Format: Provide scripts.
  • B. Role: Act as a software engineer. | Context: You are testing registration logic. | Instruction: Create Python scripts to verify endpoint behavior. | Input Data: POST /api/register with test users. | Constraints: Add checks for status codes. | Output Format: Deliver functional scripts.
  • C. Role: Act as an automation tester. | Context: You are validating an API endpoint. | Instruction: Generate Python test scripts that send POST requests and validate responses. | Input Data: User credentials. | Constraints: Include basic scenarios with asserts. | Output Format: Provide organized scripts.
  • D. Role: Act as a test automation engineer with API testing experience. | Context: You are verifying user registration that enforces field and format validation. | Instruction: Generate pytest scripts using requests for both positive (valid) and negative (invalid email, weak password, missing fields) cases. | Input Data: POST /api/register with validation rules for email and password length. | Constraints:
    Include fixtures, clear assertions, and naming consistent with pytest. | Output Format: Return complete Python test files.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #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. 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
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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