A team is testing an AI-based recommendation system. The input parameters are: user age group (young, adult, senior), content type (video, article), and device (mobile, desktop). They generate a pairwise test set and execute it. What should they do next to ensure the test set is effective?

Run the test cases in a random order to avoid bias

Add more test cases to cover all possible combinations

Verify that every pair of parameter values appears in at least one test case

Execute the test cases only on the most common device

Which of the following is a characteristic of AI-based systems that pairwise testing should account for?

The system may have a large number of input parameters, including data attributes and model settings

The system's output is deterministic and always the same for a given input

The system's behavior is independent of the training data

The system only has one or two input parameters

A team is testing an AI model that classifies customer feedback. The parameters are: feedback length (short, long), sentiment (positive, negative), and channel (email, chat, phone). The team has a budget for 8 test cases. They want to use pairwise testing. What should they do?

Run 8 random test cases instead of pairwise

Reduce the number of values for each parameter to fit the budget

Generate a pairwise test set and verify it fits within the budget

Use exhaustive testing because the budget is too small

A team is testing an AI model that predicts customer churn. The parameters are: customer age (young, middle, senior), subscription type (basic, premium), and usage level (low, high). They generate a pairwise test set and execute it. What is the most important limitation of this approach?

It requires more test cases than exhaustive testing

It may miss defects that require a specific combination of three or more parameter values

It cannot be applied to AI-based systems

It only covers one parameter at a time

Certified Tester AI Testing

Domain 9Objective 3

Hands-On Exercise: Pairwise Testing CT-AI Practice Questions (Page 1)

Part of the Domain 9: Methods and Techniques for the Testing of AI-Based Systems domain, which makes up ~13% of our current practice bank. ISTQB does not publish an official question count, but from its 60-minute exam (~25–40 total, ~3–5 in this domain), expect 1–1 from this objective — we provide 20 practice questions to prepare you well beyond it. (estimate)

20questions here

4free pages

5concepts

Questions 1–5

1application · medium
A team is testing an AI-based recommendation system. The input parameters are: user age group (young, adult, senior), content type (video, article), and device (mobile, desktop). They generate a pairwise test set and execute it. What should they do next to ensure the test set is effective?
Select an answer first
2foundation · easy
Which of the following is a characteristic of AI-based systems that pairwise testing should account for?
Select an answer first
3application · medium
A team is testing an AI model that classifies customer feedback. The parameters are: feedback length (short, long), sentiment (positive, negative), and channel (email, chat, phone). The team has a budget for 8 test cases. They want to use pairwise testing. What should they do?
Select an answer first
4application · medium
A team is testing an AI model that predicts customer churn. The parameters are: customer age (young, middle, senior), subscription type (basic, premium), and usage level (low, high). They generate a pairwise test set and execute it. What is the most important limitation of this approach?
Select an answer first
5expert · hard
A team is testing a model with 4 parameters: A (A1, A2), B (B1, B2), C (C1, C2), and D (D1, D2). They generate a pairwise test set. What is the minimum number of test cases needed to cover all pairs?
Select an answer first

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