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

1. 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 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.
C) 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.
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.

2. An LLM prioritizes tests using likelihood X impact but ranks a trivial tooltip change above a payment failure.
What defect does this MOST LIKELY show?

A) No defect; this is acceptable
B) Hallucination
C) Reasoning error in risk calculation logic
D) Dataset bias toward UI features

3. Which option BEST differentiates the three prompting techniques?

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

4. Which standard specifies requirements for managing AI systems within an organization, supporting consistent GenAI use in testing?

A) ISO/IEC 23053:2022
B) ISO/IEC 42001:2023
C) EU AI Act
D) NIST AI RMF 1.0

5. What is a key data-related aspect when defining a GenAI strategy for testing?

A) Aggregate data from all available organizational repositories without filtration
B) Prioritize accurate and relevant input data secured through defined quality procedures
C) Use only auto-generated synthetic data to avoid dependency on enterprise repositories
D) Neglect legacy data sources as they provide limited immediate relevance to testing tasks

Solutions: