A test analyst uses generative AI to map test cases to requirements. The AI produces a traceability matrix, but the analyst notices that some test cases are mapped to multiple requirements. What is the best action?

Accept the mapping because it shows thorough coverage.

Ignore the multiple mappings because they are not important.

Review the mappings to ensure they are correct and adjust if needed.

Ask the AI to map each test case to only one requirement.

What is the purpose of traceability in software testing?

To track the execution time of each test case.

To store test data in a database.

To record the names of testers.

To map test cases to requirements to ensure coverage.

What is a primary reason to use generative AI for test data generation?

To create large volumes of realistic data quickly.

To guarantee that all data is unique.

To eliminate the need for data validation.

To replace the need for test environments.

A team is using generative AI to define test oracles for a system with ambiguous specifications. The AI suggests an oracle based on a similar system's behavior. What is the best course of action?

Use the AI oracle and document it as an assumption.

Use the AI-suggested oracle because it is based on a proven system.

Clarify the specifications with stakeholders before finalizing the oracle.

Ask the AI to generate multiple oracles and use the most common one.

A team is using generative AI to define test oracles for a legacy system with incomplete specifications. The AI suggests an oracle based on the current behavior of the system. However, the team suspects the current behavior may contain bugs. What is the best approach?

Ask the AI to generate multiple oracles and select the one that matches the most test cases.

Use the AI oracle but only for positive test cases, and manually define oracles for negative cases.

Use the AI-suggested oracle as-is because it reflects the actual system behavior.

Manually define the oracle based on the intended behavior from available documentation and stakeholder input.

Certified Tester Testing with Generative AI

Domain 2Objective 4

Test Analysis with Generative AI CT-GENAI Practice Questions (Page 5)

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 26 practice questions to prepare you well beyond it. (estimate)

26questions here

6free pages

8concepts

Questions 21–25

21application · medium
A test analyst uses generative AI to map test cases to requirements. The AI produces a traceability matrix, but the analyst notices that some test cases are mapped to multiple requirements. What is the best action?
Select an answer first
22foundation · medium
What is the purpose of traceability in software testing?
Select an answer first
23foundation · medium
What is a primary reason to use generative AI for test data generation?
Select an answer first
24expert · hard
A team is using generative AI to define test oracles for a system with ambiguous specifications. The AI suggests an oracle based on a similar system's behavior. What is the best course of action?
Select an answer first
25expert · hard
A team is using generative AI to define test oracles for a legacy system with incomplete specifications. The AI suggests an oracle based on the current behavior of the system. However, the team suspects the current behavior may contain bugs. What is the best approach?
Select an answer first

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