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| Certification Vendor: | ISTQB |
|---|---|
| Exam Name: | ISTQB Certified Tester AI Testing (CT-AI) Exam |
| Exam Number: | CT-AI |
| Related Certifications: | ISTQB Certified Tester Foundation Level (CTFL) |
| Exam Duration: | 60 minutes |
| Certificate Validity Period: | Lifetime |
| Available Languages: | English |
| Real Exam Qty: | 40 |
| Exam Format: | Multiple Choice |
| Passing Score: | 65% |
| 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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質問 # 84
Which ONE of the following statements is MOST true in relation to A/B testing?
正解：B
解説：
The correct answer is D . The CT-AI syllabus defines A/B testing as a method where the responses of two variants of a program, A and B, are compared using the same inputs to determine which variant is better. It is a statistical testing approach that typically compares results across several runs. The syllabus also states that a major difference between A/B testing and back-to-back testing is that A/B testing compares two variants of the same system, whereas back-to-back testing is used to detect defects.
Option A is incorrect because A/B testing does not generate test cases and gives no guidance on how tests should be designed, although operational inputs may be used. Option B is more characteristic of back-to-back testing, which uses a pseudo-oracle for defect detection. Option C is incorrect because production or operational inputs are often used, and the syllabus gives examples of e-commerce and web companies using A
/B testing in production to compare consumer responses. Therefore, comparison of two system variants is the defining feature.
References/topics: CT-AI Syllabus Chapter 9, Section 9.4 "A/B Testing"; Section 9.7 "Selecting Test Techniques for AI-Based Systems."
質問 # 85
Which TWO of the below examples of systems BEST describe regression?
I. Predicting the age of a person
II. Predicting if someone is aged over 18
III. Predicting how much fuel is required for a journey
IV. Predicting whether a release will pass all required tests
正解：D
解説：
Regression is used for predicting continuous values.
I (Predicting the age of a person) and III (Predicting how much fuel is required for a journey) both involve continuous numerical predictions, which are characteristic of regression models.
II (Predicting if someone is aged over 18) and IV (Predicting whether a release will pass all required tests) are classification problems as they involve categorical outcomes (yes/no).
質問 # 86
Which of the below is NOT a characteristic that makes it difficult to use AI based systems?
正解：B
解説：
The correct answer is B. Lack of standards . In the CT-AI syllabus discussion of safety and AI, the listed characteristics that make it more difficult to ensure AI-based systems are safe include complexity , non- determinism , probabilistic nature , self-learning , lack of transparency, interpretability and explainability , and lack of robustness . Therefore, options A, C, and D are directly aligned with the syllabus list.
"Lack of standards" may be relevant to governance, regulation, or organizational maturity, but it is not one of the syllabus-listed intrinsic characteristics that makes AI-based systems difficult to use in safety-related applications. The syllabus separately discusses standards and regulations in Chapter 1, including ISO/IEC work, GDPR, automotive safety standards, and related regulatory contexts. However, this does not make
"lack of standards" the correct answer for this specific question. The question is targeting the safety-related AI characteristics in Chapter 2, not the broader standards landscape.
References/topics: CT-AI Syllabus Chapter 2, Section 2.8 "Safety and AI."
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質問 # 87
Which of the following describes the AI effect?
正解：A
解説：
The AI Effectis clearly defined in the ISTQB Certified Tester AI Testing Syllabus v1.0 under Section1.1 - Definition of AI and AI Effect. The document explains that society's understanding of what qualifies as "AI" changes over time. Technologies once considered AI--such as expert systems from the 1970s and 1980s or early chess-playing systems--are no longer viewed as AI today. This phenomenon is explicitly labeled the"AI Effect,"described as"the changing perception of what constitutes AI ."The syllabus states that as AI capabilities become routine or widely implemented, they often stop being perceived as true artificial intelligence .
質問 # 88
Which ONE of the following requirements for an AI based system is MOST likely to cause a challenge for testing?
正解：A
解説：
The correct answer is C . A requirement that an AI-based system be 100% accurate with no tolerance for failure creates a major testing challenge because many AI-based systems are probabilistic and may require accuracy tolerances rather than absolute expected outcomes. The CT-AI syllabus states that the probabilistic nature of many AI-based systems can make it necessary to specify tolerances for quality requirements such as prediction accuracy.
Option A is also challenging because natural language interfaces increase flexibility and make it difficult to document all possible interactions, but it is not as absolute as requiring perfect accuracy. Option B is a conventional performance efficiency requirement and can normally be tested using timing and resource measurements. Option D relates to autonomy and may require scenario-based testing, but it is still testable if the operational envelope and failure conditions are well specified. The decisive issue with option C is that it provides no tolerance range, no probabilistic acceptance model, and no practical allowance for statistical uncertainty. This creates both a specification problem and a test oracle problem.
References/topics: CT-AI Syllabus Chapter 7, Section 7.1 "Specification of AI-Based Systems"; Chapter
8, Section 8.4 "Challenges Testing Probabilistic and Non-Deterministic AI-Based Systems."
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質問 # 89
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