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

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

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

2. When an organization uses an AI chatbot for testing, what is the PRIMARY LLMOps concern?

A) Focusing primarily on user experience improvements and response formatting
B) Maximizing scalability by deploying larger cloud-based LLM clusters
C) Maintaining data privacy and minimizing security risks from external services
D) Achieving faster responses by reducing model checkpoints and updates

3. 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 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.
B) 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.
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 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.

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

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

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

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

Solutions: