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| Certification Vendor: | ISTQB |
|---|---|
| Exam Name: | ISTQB Certified Tester AI Testing (CT-AI) Exam |
| Exam Number: | CT-AI |
| Certificate Validity Period: | Lifetime |
| Real Exam Qty: | 40 |
| Exam Duration: | 60 minutes |
| Available Languages: | English |
| Related Certifications: | ISTQB Certified Tester Foundation Level (CTFL) |
| Passing Score: | 65% |
| Exam Format: | Multiple Choice |
| Recommended Training: | ISTQB Accredited Training Providers |
| Exam Registration: | ISTQB Official Website |
| Sample Questions: | ISTQB CT-AI Sample Questions |
| Exam Way: | Online and onsite proctored exam via accredited ISTQB examination providers |
| Pre Condition: | Recommended prior knowledge of ISTQB Foundation Level (CTFL) and basic understanding of software testing concepts and machine learning fundamentals. |
| Official Syllabus URL: | https://www.istqb.org |
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NEW QUESTION # 98
Which of the following statements regarding experience-based testing for AI-based systems is correct?
Choose ONE option (1 out of 4)
Answer: D
Explanation:
The ISTQB CT-AI syllabus explains inSection 4.4 - Experience-Based Testing for AI Systemsthat AI- based systems frequently suffer frominsufficient specifications, unpredictable model behavior, andtest oracle problems, especially when outputs depend on probabilistic or learned patterns. The syllabus explicitly states thatexploratory testingis especially valuable in such contexts because it allows testers to investigate the system interactively, observe unexpected behavior, and evaluate system responses that cannot be fully predicted beforehand. Thus, OptionCaccurately reflects the role and justification of exploratory testing for AI systems.
Option A describes data analysis rather than intuitive test design. Option B is incorrect because checklist- based testing does not dynamically adapt test cases; instead, it follows predetermined checklists. Option D incorrectly defines "tour-based testing"; tours refer to structured exploratory approaches, not biased datasets.
Therefore,Option Cis the syllabus-aligned correct statement.
NEW QUESTION # 99
"BioSearch" is creating an Al model used for predicting cancer occurrence via examining X-Ray images. The accuracy of the model in isolation has been found to be good. However, the users of the model started complaining of the poor quality of results, especially inability to detect real cancer cases, when put to practice in the diagnosis lab, leading to stopping of the usage of the model.
A testing expert was called in to find the deficiencies in the test planning which led to the above scenario.
Which ONE of the following options would you expect to MOST likely be the reason to be discovered by the test expert?
SELECT ONE OPTION
Answer: A
Explanation:
The question asks which deficiency is most likely to be discovered by the test expert given the scenario of poor real-world performance despite good isolated accuracy.
* A lack of similarity between the training and testing data (A): This is a common issue in ML where the model performs well on training data but poorly on real-world data due to a lack of representativeness in the training data. This leads to poor generalization to new, unseen data.
* The input data has not been tested for quality prior to use for testing (B): While data quality is important, this option is less likely to be the primary reason for the described issue compared to the representativeness of training data.
* A lack of focus on choosing the right functional-performance metrics (C): Proper metrics are crucial, but the issue described seems more related to the data mismatch rather than metric selection.
* A lack of focus on non-functional requirements testing (D): Non-functional requirements are important, but the scenario specifically mentions issues with detecting real cancer cases, pointing more towards data issues.
:
ISTQB CT-AI Syllabus Section 4.2 on Training, Validation, and Test Datasets emphasizes the importance of using representative datasets to ensure the model generalizes well to real-world data.
Sample Exam Questions document, Question #40 addresses issues related to data representativeness and model generalization.
NEW QUESTION # 100
A robotic AI based system is being built by a logistics company to operate within its unmanned warehouses.
The warehouses can all be very different and new ones are being added each year. It is expected that the system will not require retraining for each warehouse, and will be able to learn the location of different items and move them to specified locations on request. Which ONE of the following attributes should be MOST carefully considered when specifying the objectives and acceptance criteria for the system?
Answer: B
Explanation:
The correct answer is B. Adaptability . The scenario emphasizes different warehouse layouts, new warehouses being added, and the expectation that the robotic system will operate without retraining for each environment. The CT-AI syllabus defines adaptability as the ease with which a system can be modified for new situations, including different hardware and changing operational environments. It states that flexibility and adaptability are useful where the operational environment is not fully known, the system must cope with new operational environments, the system is expected to adapt to new situations, or it must determine when to change behaviour.
In this logistics context, acceptance criteria should specify how the robot adapts to unfamiliar warehouse structures, how quickly it learns item locations, what resources it may consume while adapting, and whether it still meets functional and non-functional requirements after adaptation. Option A is less central because the example does not involve fairness across protected or stakeholder groups. Option C is always relevant but not the main technical acceptance attribute. Option D may matter, but the dominant requirement is adaptation to changing environments.
References/topics: CT-AI Syllabus Chapter 2, Section 2.1 "Flexibility and Adaptability"; Chapter 8, Section 8.8 "Test Objectives and Acceptance Criteria."
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NEW QUESTION # 101
Which ONE of the following types of coverage SHOULD be used if test cases need to cause each neuron to achieve both positive and negative activation values?
Answer: B
Explanation:
Coverage for Neuron Activation Values: Sign change coverage is used to ensure that test cases cause each neuron to achieve both positive and negative activation values. This type of coverage ensures that the neurons are thoroughly tested under different activation states.
NEW QUESTION # 102
Which ONE of the following tests is LEAST likely to be performed during the ML model testing phase?
SELECT ONE OPTION
Answer: A
Explanation:
The question asks which test is least likely to be performed during the ML model testing phase. Let's consider each option:
* Testing the accuracy of the classification model (A): Accuracy testing is a fundamental part of the ML model testing phase. It ensures that the model correctly classifies the data as intended and meets the required performance metrics.
* Testing the API of the service powered by the ML model (B): Testing the API is crucial, especially if the ML model is deployed as part of a service. This ensures that the service integrates well with other systems and that the API performs as expected.
* Testing the speed of the training of the model (C): This is least likely to be part of the ML model testing phase. The speed of training is more relevant during the development phase when optimizing and tuning the model. During testing, the focus is more on the model's performance and behavior rather than how quickly it was trained.
* Testing the speed of the prediction by the model (D): Testing the speed of prediction is important to ensure that the model meets performance requirements in a production environment, especially for real- time applications.
References:
* ISTQB CT-AI Syllabus Section 3.2 on ML Workflow and Section 5 on ML Functional Performance Metrics discuss the focus of testing during the model testing phase, which includes accuracy and prediction speed but not the training speed.
NEW QUESTION # 103
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