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

1. Which statement BEST differentiates an LLM-powered test infrastructure from a traditional chatbot system used in testing?

A) It focuses primarily on visual dashboards and user navigation features
B) It produces scripted conversational responses similar to traditional bots
C) It dynamically generates test insights using contextual information
D) It provides fixed responses from predefined rule sets and scripts

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

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

3. What does an embedding represent in an LLM?

A) Numerical vectors capturing semantic relationships
B) Logical rules for reasoning
C) Tokens grouped into context windows
D) A set of test cases for validation

4. Which factor MOST influences the overall energy consumption of a Generative AI model used in software testing tasks?

A) The duration of user sessions primarily affects latency but not power efficiency
B) The type of cloud platform affects processing speed but not total energy draw
C) The location of the data center determines model bias and accuracy levels
D) The number of tokens processed directly determines the carbon intensity of each query

5. 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 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.
B) 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.
C) 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.
D) 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.

Solutions: