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

  • Exam Code: CT-GenAI
  • Exam Name: ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0
  • Updated: Jul 30, 2026
  • Q & A: 42 Questions and Answers

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ISQI CT-GenAI Exam Syllabus Topics:

SectionObjectives
Application of GenAI in Software Testing- Practical use in testing workflows
  • 1. Regression suite optimization
    • 2. Test data generation and augmentation
      • 3. Test case generation using LLMs
        • 4. Defect report analysis and summarization
          Foundations of Generative AI and LLMs- Introduction to Generative AI in Software Testing
          • 1. LLM basics, tokenization, context window, multimodal models
            • 2. Difference between chatbots and LLM-based test tools
              Risk, Quality, and Limitations of GenAI- Risks in GenAI usage
              • 1. Environmental and energy considerations
                • 2. Hallucinations and reasoning errors
                  • 3. Bias and fairness issues
                    • 4. Data privacy and security concerns
                      Organizational Adoption and Governance- Enterprise GenAI adoption
                      • 1. Integration into CI/CD pipelines
                        • 2. Policy, ethics, and compliance considerations
                          • 3. LLMOps and governance models
                            Prompt Engineering for Testing- Prompt design techniques
                            • 1. Structuring prompts for test case generation
                              • 2. Zero-shot, one-shot, few-shot prompting
                                • 3. Prompt chaining and meta prompting

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

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

                                  A) Maintaining static documentation repositories without real-time prompt standardization processes
                                  B) Applying a reusable and structured template that guides GenAI models toward consistent outputs
                                  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


                                  2. In the context of software testing, which statements (i-v) about foundation, instruction-tuned, and reasoning LLMs are CORRECT?
                                  i. Foundation LLMs are best suited for broad exploratory ideation when test requirements are underspecified.
                                  ii. Instruction-tuned LLMs are strongest at adhering to fixed test case formats (e.g., Gherkin) from clear prompts.
                                  iii. Reasoning LLMs are strongest at multi-step root-cause analysis across logs, defects, and requirements.
                                  iv. Foundation LLMs are optimal for strict policy compliance and template conformance.
                                  v. Instruction-tuned LLMs can follow stepwise reasoning without any additional training or prompting.

                                  A) i, ii, iii
                                  B) i, ii, iii (Duplicate entry in original source)
                                  C) ii, iii, iv
                                  D) i, iii, v


                                  3. What distinguishes an LLM-powered agent from a basic AI chatbot in test processes?

                                  A) Use of a conversational tone and improved response personalization
                                  B) Ability to trigger automated actions beyond conversation
                                  C) Ability to respond to prompts without explicit user instructions
                                  D) Reliance on predefined templates to generate short, factual answers


                                  4. When an organization uses an AI chatbot for testing, what is the PRIMARY LLMOps concern?

                                  A) Focusing primarily on user experience improvements and response formatting
                                  B) Maintaining data privacy and minimizing security risks from external services
                                  C) Maximizing scalability by deploying larger cloud-based LLM clusters
                                  D) Achieving faster responses by reducing model checkpoints and updates


                                  5. You are tasked with applying structured prompting to perform impact analysis on recent code changes. Which of the following improvements would BEST align the prompt with structured prompt engineering best practices for comprehensive impact analysis?

                                  A) Include mapping code changes to affected modules, identifying test cases, prioritizing by risk level and change complexity
                                  B) Include references to version control systems like Git in the constraints.
                                  C) Add a step to review the change log for syntax errors before analysis.
                                  D) Specify that the role is a test architect specializing in CI/CD pipelines.


                                  Solutions:

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

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