A business analyst provides a requirements document for a new search feature. The team uses a generative AI tool to create test cases. The AI generates test cases that cover the search functionality but miss the 'no results' scenario. What is the most likely reason for this omission?

The AI tool is biased toward positive test cases

The requirements document does not explicitly mention the 'no results' scenario

The AI tool is not capable of generating negative test cases

The team did not run the AI tool long enough

A tester wants to use generative AI to support test design for a new feature. Which activity is most directly supported by generative AI?

Generating a list of boundary values and equivalence partitions from the feature's input rules

Deciding which test management tool the team should adopt

Creating a test environment with the required hardware and software

Running regression tests and comparing actual results with expected results

A tester needs to generate test data for a system that processes customer addresses. The system has a field for postal code that must match a specific format (e.g., 5 digits for US). The tester uses a generative AI tool to create test data. What is the best way to ensure the generated postal codes are valid?

Use the AI tool to generate postal codes and then validate them with a separate script

Provide the AI tool with a clear description of the postal code format and examples of valid codes

Generate all postal codes manually to ensure accuracy

Use the AI tool to generate random numbers and accept them as postal codes

A team uses a generative AI tool to create test cases from a user story that includes acceptance criteria. The AI generates test cases that cover the acceptance criteria but also includes many additional test cases that are not directly traceable to any requirement. The team has a strict policy that all test cases must be traceable to requirements. What is the best approach?

Review the untraceable test cases and, if they are valuable, update the requirements to include them

Keep all AI-generated test cases because they may uncover defects

Ask the AI to generate only test cases that are traceable to the acceptance criteria

Delete all AI-generated test cases that are not traceable to the acceptance criteria

What is a key benefit of using generative AI to create test data?

It can produce a wide variety of data values, including edge cases, without manual effort

It eliminates the need for any test data validation

It automatically deploys the test data to production

It guarantees that all test data is free from any errors

Certified Tester Testing with Generative AI

Domain 2Objective 5

Test Design and Test Implementation with Generative AI CT-GENAI Practice Questions (Page 4)

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)

31questions here

7free pages

8concepts

Questions 16–20

16application · medium
A business analyst provides a requirements document for a new search feature. The team uses a generative AI tool to create test cases. The AI generates test cases that cover the search functionality but miss the 'no results' scenario. What is the most likely reason for this omission?
Select an answer first
17foundation · easy
A tester wants to use generative AI to support test design for a new feature. Which activity is most directly supported by generative AI?
Select an answer first
18application · medium
A tester needs to generate test data for a system that processes customer addresses. The system has a field for postal code that must match a specific format (e.g., 5 digits for US). The tester uses a generative AI tool to create test data. What is the best way to ensure the generated postal codes are valid?
Select an answer first
19expert · hard
A team uses a generative AI tool to create test cases from a user story that includes acceptance criteria. The AI generates test cases that cover the acceptance criteria but also includes many additional test cases that are not directly traceable to any requirement. The team has a strict policy that all test cases must be traceable to requirements. What is the best approach?
Select an answer first
20foundation · easy
What is a key benefit of using generative AI to create test data?
Select an answer first

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Test Design and Test Implementation with Generative AI CT-GENAI Practice Questions (Page 4)

Questions 16–20

A business analyst provides a requirements document for a new search feature. The team uses a generative AI tool to create test cases. The AI generates test cases that cover the search functionality but miss the 'no results' scenario. What is the most likely reason for this omission?

A tester wants to use generative AI to support test design for a new feature. Which activity is most directly supported by generative AI?

What is a key benefit of using generative AI to create test data?

Keep studying — Prompt Engineering for Effective Software Testing