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ISQI CT-GenAI Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Prompt Engineering for Testing | - Prompt design techniques
|
| Organizational Adoption and Governance | - Enterprise GenAI adoption
|
| Application of GenAI in Software Testing | - Practical use in testing workflows
|
| Foundations of Generative AI and LLMs | - Introduction to Generative AI in Software Testing
|
| Risk, Quality, and Limitations of GenAI | - Risks in GenAI usage
|
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) iv -> i -> iii -> ii
B) i -> iv -> iii -> ii
C) iv -> iii -> i -> ii
D) iii -> iv -> i -> ii
2. Which statement BEST contrasts interaction style and scope?
A) Chatbots enforce fixed workflows; LLM apps support free-form exploration beneficial for software testing
B) Both are identical aside from UI theme.
C) Chatbots enable conversational interactions; LLM apps provide capabilities for defined test tasks.
D) Chatbots require API integration; LLM apps do not.
3. 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) Specify that the role is a test architect specializing in CI/CD pipelines.
B) Include references to version control systems like Git in the constraints.
C) Include mapping code changes to affected modules, identifying test cases, prioritizing by risk level and change complexity
D) Add a step to review the change log for syntax errors before analysis.
4. Which concept refers to breaking text into smaller units for processing by LLMs?
A) Tokenization
B) Context Window
C) Embeddings
D) Transformer
5. Which setting can reduce variability by narrowing the sampling distribution during inference?
A) Increasing temperature
B) Increasing learning rate
C) Using a larger context window
D) Lowering temperature
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: D |



