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ISQI CT-GenAI Exam Syllabus Topics:

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

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

                                  1. You must generate test cases for a new payments rule. The system includes API specifications stored in a vector database and prior tests in a relational database. Which of the following sequences BEST represents the correct order for applying a Retrieval-Augmented Generation (RAG) workflow?
                                  i. Retrieve semantically similar specification chunks from the vector database ii. Feed both retrieved datasets as context for the LLM to generate new test cases iii. Retrieve relevant historical cases from the relational database iv. Submit a focused query describing the new test requirement

                                  A) iii -> iv -> i -> ii
                                  B) iv -> i -> iii -> ii
                                  C) i -> iv -> iii -> ii
                                  D) iv -> iii -> i -> ii


                                  2. Which statement about data privacy risks in GenAI-assisted testing is INCORRECT?

                                  A) Using GenAI without regulatory compliance can lead to legal exposure
                                  B) Some GenAI tools may store/process data without explicit consent
                                  C) GenAI outputs can accidentally reveal sensitive information present in inputs
                                  D) Strict GDPR compliance eliminates all privacy risk


                                  3. A tester uploads crafted images that steer the LLM into validating non-existent acceptance criteria. Which attack vector is this?

                                  A) Data exfiltration
                                  B) Data poisoning
                                  C) Request manipulation
                                  D) Malicious code generation


                                  4. Which AI approach requires feature engineering and structured data preparation?

                                  A) Generative AI
                                  B) Symbolic AI
                                  C) Classical Machine Learning
                                  D) Deep Learning


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

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


                                  Solutions:

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

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