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ISQI CT-GenAI Exam Syllabus Topics:

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

2. 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 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.
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.

3. Which statement BEST contrasts interaction style and scope?

A) Chatbots enforce fixed workflows; LLM apps support free-form exploration beneficial for software testing
B) Chatbots require API integration; LLM apps do not.
C) Both are identical aside from UI theme.
D) Chatbots enable conversational interactions; LLM apps provide capabilities for defined test tasks.

4. Which statement about data privacy risks in GenAI-assisted testing is INCORRECT?

A) Some GenAI tools may store/process data without explicit consent
B) Strict GDPR compliance eliminates all privacy risk
C) GenAI outputs can accidentally reveal sensitive information present in inputs
D) Using GenAI without regulatory compliance can lead to legal exposure

5. 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 provides fixed responses from predefined rule sets and scripts
C) It produces scripted conversational responses similar to traditional bots
D) It dynamically generates test insights using contextual information

Solutions: