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ISQI CT-GenAI Exam Syllabus Topics:

SectionObjectives
Prompt Engineering for Testing- Prompt design techniques
  • 1. Prompt chaining and meta prompting
    • 2. Structuring prompts for test case generation
      • 3. Zero-shot, one-shot, few-shot prompting
        Organizational Adoption and Governance- Enterprise GenAI adoption
        • 1. LLMOps and governance models
          • 2. Policy, ethics, and compliance considerations
            • 3. Integration into CI/CD pipelines
              Application of GenAI in Software Testing- Practical use in testing workflows
              • 1. Regression suite optimization
                • 2. Defect report analysis and summarization
                  • 3. Test data generation and augmentation
                    • 4. Test case generation using LLMs
                      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. Data privacy and security concerns
                            • 2. Environmental and energy considerations
                              • 3. Hallucinations and reasoning errors
                                • 4. Bias and fairness issues

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

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

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


                                  2. Which option BEST differentiates the three prompting techniques?

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


                                  3. Who typically defines the system prompt in a testing workflow?

                                  A) End user during normal chat use
                                  B) A tester configuring the assistant
                                  C) CI server automatically without human input
                                  D) Product owner in user stories only


                                  4. Which statement BEST describes vision-language models (VLMs)?

                                  A) VLMs are a subset of multimodal LLMs integrating visual and textual information.
                                  B) VLMs process audio and video but not images.
                                  C) VLMs are a superset of multimodal LLMs.
                                  D) VLMs are unrelated to multimodal LLMs and focus only on UI automation.


                                  5. You are using an LLM to assist in analyzing test execution trends to predict potential risks. Which of the following improvements would BEST enhance the LLM's ability to predict risks and provide actionable alerts?

                                  A) Expand the output format to include risk predictions with severity levels, recommended actions, and a timeline for team intervention based on trend analysis.
                                  B) Emphasize constraints that focus on deviations that could impact release timelines or quality gates.
                                  C) Add an instruction to calculate statistical variance and highlight tests that deviate by more than 20% from baseline metrics.
                                  D) Specify that the role is a test analyst with expertise in predictive analytics and risk management.


                                  Solutions:

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

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