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CT-AI ISTQBCertified Tester AI Testing Exam Questions and Answers

Questions 4

A wildlife conservation group would like to use a neural network to classify images of different animals. The algorithm is going to be used on a social media platform to automatically pick out pictures of the chosen animal of the month. This month’s animal is set to be a wolf. The test team has already observed that the algorithm could classify a picture of a dog as being a wolf because of the similar characteristics between dogs and wolves. To handle such instances, the team is planning to train the model with additional images of wolves and dogs so that the model is able to better differentiate between the two.

What test method should you use to verify that the model has improved after the additional training?

Options:

A.

Metamorphic testing because the application domain is not clearly understood at this point

B.

Adversarial testing to verify that no incorrect images have been used in the training

C.

Pairwise testing using combinatorics to look at a long list of photo parameters

D.

Back-to-back testing using the version of the model before training and the new version of the model after being trained with additional images

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Questions 5

A software component uses machine learning to recognize the digits from a scan of handwritten numbers. In the scenario above, which type of Machine Learning (ML) is this an example of?

SELECT ONE OPTION

Options:

A.

Reinforcement learning

B.

Regression

C.

Classification

D.

Clustering

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Questions 6

Which of the following is one of the reasons for data mislabelling?

Options:

A.

Lack of domain knowledge

B.

Expert knowledge

C.

Interoperability error

D.

Small datasets

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Questions 7

A startup company has implemented a new facial recognition system for a banking application for mobile devices. The application is intended to learn at run-time on the device to determine if the user should be granted access. It also sends feedback over the Internet to the application developers. The application deployment resulted in continuous restarts of the mobile devices.

Which of the following is the most likely cause of the failure?

Options:

A.

The feedback requires a physical connection and cannot be sent over the Internet

B.

Mobile operating systems cannot process machine learning algorithms

C.

The size of the application is consuming too much of the phone's storage capacity

D.

The training, processing, and diagnostic generation are too computationally intensive for the mobile device hardware to handle

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Questions 8

There is a growing backlog of unresolved defects for your project. You know the developers have an ML model that they have created which has learned which developers work on which type of software and the speed with which they resolve issues. How could you use this model to help reduce the backlog and implement more efficient defect resolution?

Options:

A.

Use it to prioritize defects automatically based on the time expected for the fix to be made, the speed of the fix, and the likelihood of regressions

B.

Use it to assign defects to the best developer to resolve the problem and to load balance the defect assignments among the developers

C.

Use it to determine the root cause of each defect and develop a process improvement plan that can be implemented to remove the most common root causes

D.

Use it to review the code and determine where more defects are likely to occur so that testing can be targeted to those areas

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Questions 9

Which ONE of the following options describes the LEAST LIKELY usage of Al for detection of GUI changes due to changes in test objects?

SELECT ONE OPTION

Options:

A.

Using a pixel comparison of the GUI before and after the change to check the differences.

B.

Using a computer vision to compare the GUI before and after the test object changes.

C.

Using a vision-based detection of the GUI layout changes before and after test object changes.

D.

Using a ML-based classifier to flag if changes in GUI are to be flagged for humans.

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Questions 10

You have access to the training data that was used to train an AI-based system. You can review this information and use it as a guideline when creating your tests. What type of characteristic is this?

Options:

A.

Autonomy

B.

Explorability

C.

Transparency

D.

Accessibility

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Questions 11

Pairwise testing can be used in the context of self-driving cars for controlling an explosion in the number of combinations of parameters.

Which ONE of the following options is LEAST likely to be a reason for this incredible growth of parameters?

SELECT ONE OPTION

Options:

A.

Different Road Types

B.

Different weather conditions

C.

ML model metrics to evaluate the functional performance

D.

Different features like ADAS, Lane Change Assistance etc.

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Questions 12

A neural network has been designed and created to assist day-traders improve efficiency when buying and selling commodities in a rapidly changing market. Suppose the test team executes a test on the neural network where each neuron is examined. For this network, the shortest path indicates a "buy" and it will only occur when the one-day predicted value of the commodity is greater than the spot price by 0.75%. The neurons are stimulated by entering commodity prices and testers verify that they activate only when the future value exceeds the spot price by at least 0.75%.

Which of the following statements BEST explains the type of coverage being tested on the neural network?

Options:

A.

Threshold coverage

B.

Neuron coverage

C.

Sign-change coverage

D.

Value-change coverage

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Questions 13

Which of the following aspects is a challenge when handling test data for an AI-based system?

Options:

A.

Personal data or confidential data

B.

Output data or intermediate data

C.

Video frame speed or aspect ratio

D.

Data frameworks or machine learning frameworks

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Questions 14

Which ONE of the following options is an example that BEST describes a system with Al-based autonomous functions?

SELECT ONE OPTION

Options:

A.

A system that utilizes human beings for all important decisions.

B.

A fully automated manufacturing plant that uses no software.

C.

A system that utilizes a tool like Selenium.

D.

A system that is fully able to respond to its environment.

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Questions 15

You are testing an autonomous vehicle which uses AI to determine proper driving actions and responses. You have evaluated the parameters and combinations to be tested and have determined that there are too many to test in the time allowed. It has been suggested that you use pairwise testing to limit the parameters. Given the complexity of the software under test, what is likely the outcome from using pairwise testing?

Options:

A.

The number of parameters to test can be reduced to less than a dozen

B.

All high priority defects will be identified using this method

C.

While the number of tests needed can be reduced, there may still be a large enough set of tests that automation will be required to execute all of them

D.

Pairwise cannot be applied to this problem because there is AI involved and the evolving values may result in unexpected results that cannot be verified

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Questions 16

Which of the following characteristics of AI-based systems make it more difficult to ensure they are safe?

Options:

A.

Simplicity

B.

Sustainability

C.

Non-determinism

D.

Robustness

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Questions 17

Before deployment of an AI-based system, a developer is expected to demonstrate in a test environment how decisions are made. Which of the following characteristics does decision making fall under?

Options:

A.

Explainability

B.

Autonomy

C.

Self-learning

D.

Non-determinism

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Questions 18

When verifying that an autonomous AI-based system is acting appropriately, which of the following are MOST important to include?

Options:

A.

Test cases to verify that the system automatically confirms the correct classification of training data

B.

Test cases to detect the system appropriately automating its data input

C.

Test cases to detect the system prompting for unnecessary human intervention

D.

Test cases to verify that the system automatically suppresses invalid output data

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Questions 19

A word processing company is developing an automatic text correction tool. A machine learning algorithm was used to develop the auto text correction feature. The testers have discovered that when they start typing “Isle of Wight” it fills in “Isle of Eight”. Several UAT testers have accepted this change without noticing. What type of bias is this?

Options:

A.

Geographical/Locality

B.

Automation/Complacency

C.

Complacency/Disregard

D.

Ignorance/Cognitive

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Questions 20

A company is using a spam filter to attempt to identify which emails should be marked as spam. Detection rules are created by the filter that causes a message to be classified as spam. An attacker wishes to have all messages internal to the company be classified as spam. So, the attacker sends messages with obvious red flags in the body of the email and modifies the "from" portion of the email to make it appear that the emails have been sent by company members. The testers plan to use exploratory data analysis (EDA) to detect the attack and use this information to prevent future adversarial attacks.

How could EDA be used to detect this attack?

Options:

A.

EDA can help detect the outlier emails from the real emails

B.

EDA can detect and remove the false emails

C.

EDA can restrict how many inputs can be provided by unique users

D.

EDA cannot be used to detect the attack

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Questions 21

A ML engineer is trying to determine the correctness of the new open-source implementation *X", of a supervised regression algorithm implementation. R-Square is one of the functional performance metrics used to determine the quality of the model.

Which ONE of the following would be an APPROPRIATE strategy to achieve this goal?

SELECT ONE OPTION

Options:

A.

Add 10% of the rows randomly and create another model and compare the R-Square scores of both the model.

B.

Train various models by changing the order of input features and verify that the R-Square score of these models vary significantly.

C.

Compare the R-Square score of the model obtained using two different implementations that utilize two different programming languages while using the same algorithm and the same training and testing data.

D.

Drop 10% of the rows randomly and create another model and compare the R-Square scores of both the models.

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Questions 22

Which ONE of the following models BEST describes a way to model defect prediction by looking at the history of bugs in modules by using code quality metrics of modules of historical versions as input?

SELECT ONE OPTION

Options:

A.

Identifying the relationship between developers and the modules developed by them.

B.

Search of similar code based on natural language processing.

C.

Clustering of similar code modules to predict based on similarity.

D.

Using a classification model to predict the presence of a defect by using code quality metrics as the input data.

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Questions 23

Which of the following is correct regarding the layers of a deep neural network?

Options:

A.

There is only an input and output layer

B.

There is at least one internal hidden layer

C.

There must be a minimum of five total layers to be considered deep

D.

The output layer is not connected with the other layers to maintain integrity

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Questions 24

A bank wants to use an algorithm to determine which applicants should be given a loan. The bank hires a data scientist to construct a logistic regression model to predict whether the applicant will repay the loan or not. The bank has enough data on past customers to randomly split the data into a training dataset and a test/validation dataset. A logistic regression model is constructed on the training dataset using the following independent variables:

    Gender

    Marital status

    Number of dependents

    Education

    Income

    Loan amount

    Loan term

    Credit score

The model reveals that those with higher credit scores and larger total incomes are more likely to repay their loans. The data scientist has suggested that there might be bias present in the model based on previous models created for other banks.

Given this information, what is the best test approach to check for potential bias in the model?

Options:

A.

Experience-based testing should be used to confirm that the training data set is operationally relevant. This can include applying exploratory data analysis (EDA) to check for bias within the training data set.

B.

Back-to-back testing should be used to compare the model created using the training data set to another model created using the test data set. If the two models significantly differ, it will indicate there is bias in the original model.

C.

Acceptance testing should be used to make sure the algorithm is suitable for the customer. The team can re-work the acceptance criteria such that the algorithm is sure to correctly predict the remaining applicants that have been set aside for the validation dataset ensuring no bias is present.

D.

A/B testing should be used to verify that the test data set does not detect any bias that might have been introduced by the original training data. If the two models significantly differ, it will indicate there is bias in the original model.

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Exam Code: CT-AI
Exam Name: ISTQBCertified Tester AI Testing Exam
Last Update: Jun 9, 2025
Questions: 80

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