A team uses a generative AI tool to generate test data for a system that handles personal data. The AI generates a dataset that appears realistic but contains combinations of names and addresses that match real individuals. The team is concerned about privacy. What is the best course of action?

Anonymize the dataset by replacing names and addresses with fictional ones

Delete the dataset and generate all test data manually

Validate the dataset against known real data and, if it matches, regenerate with a prompt that explicitly requests synthetic data

Use the dataset as-is because it is generated by AI and not real data

Which output is most typical of generative AI when used in test implementation?

A set of automated test code in a programming or scripting language

A list of test environment configuration changes

A risk assessment matrix for the project

A test execution report with pass/fail status

When integrating generative AI into the test design workflow, what should the team do first?

Identify the specific tasks where AI can add value, such as test case generation

Remove all existing test cases to make room for AI-generated ones

Immediately automate all test cases without any planning

Purchase the most expensive AI tool on the market

A developer is using a generative AI assistant to implement a unit test for a function that calculates the total price of an order, including tax and discounts. The AI suggests a test script. What is the most important aspect to verify in the AI-generated test script?

The script uses the correct assertion library

The script is formatted consistently with the project's style guide

The script's expected values match the function's specification for tax and discount calculations

A test automation engineer is using a generative AI tool to create a test script for a REST API. The AI suggests a script that uses a hard-coded base URL. What is the best practice to follow?

Hard-code the URL in a separate file and import it

Accept the script as-is because it works for the current environment

Replace the hard-coded URL with a configuration variable or environment property

Ask the AI to generate a new script without any URL

Certified Tester Testing with Generative AI

Domain 2Objective 5

Test Design and Test Implementation with Generative AI CT-GENAI Practice Questions (Page 6)

Part of the Prompt Engineering for Effective Software Testing domain, which makes up ~30% of our current practice bank. ISTQB does not publish an official question count, but from its 60-minute exam (~25–40 total, ~8–12 in this domain), expect 1–1 from this objective — we provide 31 practice questions to prepare you well beyond it. (estimate)

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Questions 26–30

26expert · hard
A team uses a generative AI tool to generate test data for a system that handles personal data. The AI generates a dataset that appears realistic but contains combinations of names and addresses that match real individuals. The team is concerned about privacy. What is the best course of action?
Select an answer first
27foundation · easy
Which output is most typical of generative AI when used in test implementation?
Select an answer first
28foundation · easy
When integrating generative AI into the test design workflow, what should the team do first?
Select an answer first
29application · medium
A developer is using a generative AI assistant to implement a unit test for a function that calculates the total price of an order, including tax and discounts. The AI suggests a test script. What is the most important aspect to verify in the AI-generated test script?
Select an answer first
30application · medium
A test automation engineer is using a generative AI tool to create a test script for a REST API. The AI suggests a script that uses a hard-coded base URL. What is the best practice to follow?
Select an answer first

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