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

1. You are using an LLM to assist in analyzing test execution trends to predict potential risks. Which of the following improvements would BEST enhance the LLM's ability to predict risks and provide actionable alerts?

A) Specify that the role is a test analyst with expertise in predictive analytics and risk management.
B) Add an instruction to calculate statistical variance and highlight tests that deviate by more than 20% from baseline metrics.
C) Expand the output format to include risk predictions with severity levels, recommended actions, and a timeline for team intervention based on trend analysis.
D) Emphasize constraints that focus on deviations that could impact release timelines or quality gates.

2. A prompt section states: "Web checkout module v3.2; focus on coupon application; existing regression suite IDs T-112-T-150; recent defect ID BUG-431." Which component is this?

A) Input data
B) Instruction
C) Constraints
D) Output format

3. Which concept refers to breaking text into smaller units for processing by LLMs?

A) Context Window
B) Transformer
C) Embeddings
D) Tokenization

4. Which statement about fine-tuning for test tasks is INCORRECT?

A) It replaces the model's general knowledge entirely and prevents overfitting
B) It adapts a pre-trained model to a domain using task-specific data
C) It can be applied to smaller SLMs to improve task performance with lower compute
D) It enhances relevance to organizational terminology and formats

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 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 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.
D) 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.

Solutions: