[2026年11月11日] CT-AI PDF問題とテストエンジンには162問があります [Q73-Q93]

Rate this post

[2026年11月11日] CT-AI PDF問題とテストエンジンには162問があります

更新された試験エンジンはCT-AI試験無料お試しサンプル365日更新されます

ISTQB CT-AI 認定試験の出題範囲：

トピック	出題範囲
トピック 1	AI ベースシステムのテストの方法とテクニック: このセクションでは、ML システムのテストが敵対的攻撃やデータ汚染の防止にどのように役立つかを説明することに重点を置いています。
トピック 2	従来のシステムに必要なものとは異なるシステムです。
トピック 3	機械学習 ML: このセクションには、教師あり学習の一部としての分類と回帰が含まれており、ML アルゴリズムの選択に関係する要因が説明され、アンダーフィッティングとオーバーフィッティングが示されます。
トピック 4	テストでの AI の使用: このセクションの試験トピックでは、ソフトウェアテストで使用される AI テクノロジーの分類について説明します。
トピック 5	AI ベースシステムの品質特性: このセクションでは、AI ベースシステムの特性としての柔軟性と適応性の重要性を説明する方法と、AI ベースシステムの進化を管理することの重要性について説明します。また、安全関連のアプリケーションで AI ベースシステムを使用することを困難にする特性を思い出す方法についても説明します。
トピック 6	AI ベースシステムのテストの概要: このセクションでは、AI ベースシステムのシステム仕様がテストでどのような課題を生み出す可能性があるかに焦点を当て、自動化のバイアスとそれがテストにどのように影響するかについて説明します。
トピック 7	AI 入門: この試験セクションでは、AI 効果やそれが AI の定義に与える影響などのトピックを取り上げます。狭義の AI、汎用 AI、スーパー AI を区別する方法を取り上げます。さらに、AI ベースのシステムに標準がどのように適用されるかを説明するトピックも取り上げます。

質問 73
Arihant Meditation is a startup using Al to aid people in deeper and better meditation based on analysis of various factors such as time and duration of the meditation, pulse and blood pressure, EEG patters etc. among others. Their model accuracy and other functional performance parameters have not yet reached their desired level.
Which ONE of the following factors is NOT a factor affecting the ML functional performance?

The data pipeline

The quality of the labeling

Biased data

The number of classes

質問 74
Which of the following is an example of overfitting?

The model is not able to generalize to accommodate new types of data.

The model is too simplistic for the data.

The model is missing relationships between the inputs and outputs.

The model discards data it considers to be noise or outliers.

質問 75
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

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

Search of similar code based on natural language processing.

Clustering of similar code modules to predict based on similarity.

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

Defect prediction models aim to identify parts of the software that are likely to contain defects by analyzing historical data and code quality metrics. The primary goal is to use this predictive information to allocate testing and maintenance resources effectively. Let’s break down why option D is the correct choice:
Understanding Classification Models:
Classification models are a type of supervised learning algorithm used to categorize or classify data into predefined classes or labels. In the context of defect prediction, the classification model would classify parts of the code as either “defective” or “non-defective” based on the input features.
Input Data – Code Quality Metrics:
The input data for these classification models typically includes various code quality metrics such as cyclomatic complexity, lines of code, number of methods, depth of inheritance, coupling between objects, etc. These metrics help the model learn patterns associated with defects.
Historical Data:
Historical versions of the code along with their defect records provide the labeled data needed for training the classification model. By analyzing this historical data, the model can learn which metrics are indicative of defects.
Why Option D is Correct:
Option D specifies using a classification model to predict the presence of defects by using code quality metrics as input data. This accurately describes the process of defect prediction using historical bug data and quality metrics.
Eliminating Other Options:
A . Identifying the relationship between developers and the modules developed by them: This does not directly involve predicting defects based on code quality metrics and historical data.
B . Search of similar code based on natural language processing: While useful for other purposes, this method does not describe defect prediction using classification models and code metrics.
C . Clustering of similar code modules to predict based on similarity: Clustering is an unsupervised learning technique and does not directly align with the supervised learning approach typically used in defect prediction models.
Reference:
ISTQB CT-AI Syllabus, Section 9.5, Metamorphic Testing (MT), describes various testing techniques including classification models for defect prediction.
“Using AI for Defect Prediction” (ISTQB CT-AI Syllabus, Section 11.5.1).

質問 76
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?

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

Mobile operating systems cannot process machine learning algorithms

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

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

質問 77
You are conducting a user acceptance test of a decision-support recommendation system used in a data processing business. In addition to testing the functional performance of the recommendation systems, what else would you be MOST likely to test?

The number of inaccurate recommendations per day

The amount of system resources consumed by each recommendation

The number of accurate recommendations per day

The accuracy of the human decision when presented with an inaccurate recommendation

質問 78
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

I, II

I, Iv

II, In

I, II

質問 79
Which ONE of the following statements correctly describes the importance of flexibility for Al systems?
SELECT ONE OPTION

Al systems are inherently flexible.

Al systems require changing of operational environments; therefore, flexibility is required.

Flexible Al systems allow for easier modification of the system as a whole.

Self-learning systems are expected to deal with new situations without explicitly having to program for it.

質問 80
A local business has a mail pickup/delivery robot for their office. The robot currently uses a track to move between pickup/drop-off locations. When it arrives at a destination, the robot stops to allow a human to remove or deposit mail. The office has decided to upgrade the robot to include AI capabilities that allow the robot to perform its duties without a track, without running into obstacles, and without human intervention.
The test team is creating a list of new and previously established test objectives and acceptance criteria to be used in the testing of the robot upgrade. Which of the following test objectives will test an AI quality characteristic for this system?

The robot must evolve to optimize its routing

The robot must recharge for no more than six hours a day

The robot must record the time of each delivery which is compiled into a report

The robot must complete 99.99% of its deliveries each day

質問 81
In a certain coffee producing region of Colombia, there have been some severe weather storms, resulting in massive losses in production. This caused a massive drop in stock price of coffee.
Which ONE of the following types of testing SHOULD be performed for a machine learning model for stock-price prediction to detect influence of such phenomenon as above on price of coffee stock.

Testing for accuracy

Testing for bias

Testing for concept drift

Testing for security

質問 82
Which of the following is an example of a clustering problem that can be resolved by unsupervised learning?

Associating shoppers with their shopping tendencies

Grouping individual fish together based on their types of fins

Classifying muffin purchases based on the perceived attractiveness of their packaging

Estimating the expected purchase of cat food after a particularly successful ad campaign

質問 83
Which of the following is THE LEAST appropriate tests to be performed for testing a feature related to autonomy?

Test for human handover to give rest to the system.

Test for human handover when it should actually not be relinquishing control.

Test for human handover requiring mandatory relinquishing control.

Test for human handover after a given time interval.

質問 84
Which ONE of the following tests is MOST likely to describe a useful test to help detect different kinds of biases in ML pipeline?
SELECT ONE OPTION

Testing the distribution shift in the training data for inappropriate bias.

Test the model during model evaluation for data bias.

Testing the data pipeline for any sources for algorithmic bias.

Check the input test data for potential sample bias.

質問 85
Which ONE of the following statements BEST describes a testing challenge that specifically applied to a self-learning system?

When systems change themselves the results of previously passing tests may change

It is necessary to test whether the system will relinquish control to a human at the right time

External data sources might be required to ensure that the system is unbiased

In can be difficult to explain the link between test inputs and outputs

質問 86
Which of the following is an example of an input change where it would be expected that the AI system should be able to adapt?

It has been trained to recognize cats and is given an image of a dog

It has been trained to recognize human faces at a particular resolution and it is given a human face image captured with a higher resolution

It has been trained to analyze mathematical models and is given a set of landscape pictures to classify

It has been trained to analyze customer buying trend data and is given information on supplier cost data

質問 87
An Al based website will recommend holiday rental accommodation for a user based on their previous bookings, and inputs about their requirements. Metamorphic testing is being used by a test engineer, who has built up a history of previous bookings. The first test case they use (T1) is as follows:

The outputs from the test ate the following accommodations:
* Villa Fianca
* Villa Palma
* Apartments Mirasol
* Villa Paris
* Apartments Miramar
Which ONE of the below options are the MOST likely outputs from the test:

T2: Villa Franca; T3: Villa Franca. Villa Palma

T2: Villa Franca; T3; Villa Palma

T2: Villa Franca, Villa Palma. Apartments Mirasol; T3: Villa Franca, Villa Paris. Apartments Miramar

T2: Villa Franca, Villa Palma. Apartments Mirasol; T3: Villa Paris. Apartments Miramar

質問 88
A car insurance company is using a new AI service to reward defensive driving behavior among its policyholders. The driving behavior is recorded in a rating number (score).
The AI service determines this score from the following input values:
Reference speed v_max in km/h
Average speed v_mean in km/h
Average acceleration a_pos in m/s²
Average braking deceleration a_neg in m/s²
The more defensive the driving behavior is (slow driving, low acceleration, low braking deceleration), the higher is the score.
Three initial test cases (Test 1 to Test 3) are used for testing the AI service. In addition, new test cases A-D are proposed.

Which of the new tests is NOT a follow-up test case for metamorphic testing?
Choose ONE option! (1 out of 4)

Test A is not a follow-up test case.

Test C is not a follow-up test case.

Test B is not a follow-up test case.

Test D is not a follow-up test case.

質問 89
Consider a natural language processing (NLP) algorithm that attempts to predict the next word that you would like to type in a text message. An update to the algorithm has been created that should increase the accuracy of the predictions based on user typing patterns. The old algorithm was rated for accuracy by the users. Then, after the new update was released, the users rated the updated algorithm. A statistical test was used to compare the two versions of the algorithm to see whether or not the update should remain in place.
This is an example of what type of testing?

Metamorphic testing

A/B testing

Exploratory testing

Pairwise testing

質問 90
How can a tester check the system for bias as part of a review of data sources, acquisition, and preprocessing?

During the review, it can uncover algorithmic bias by analysing the procedures used to obtain the training data.

During the review of the preprocessing, the auditor can uncover whether the data has been influenced in a way that could lead to sample distortions.

It may use the LIME method as part of its data collection review to detect inappropriate bias.

As part of the review of preprocessing, it can reveal whether the data has been influenced in a way that could lead to algorithmic bias.

質問 91
Which of the following neural network coverage criteria can be adapted for its application?
Choose ONE option (1 out of 4)

Sign-Sign coverage

Sign-Change coverage

Threshold coverage

Neuron coverage

質問 92
Which ONE of the following statements is MOST true in relation to A/B testing?

Many test cases can be generated

The purpose is to detect defects

Production data is not used

The purpose is to compare two variants of a system

質問 93
Which statement about AI-based test case generation is correct?
Choose ONE option (1 out of 4)

AI-generated functional test cases typically result in poor requirements coverage.

A different test oracle is usually required for each AI-generated functional test case.

Expected results may not be available for AI-generated functional test cases.

An AI-based system under test must not be used as a functional test oracle.

試験合格保証CT-AI試験には正確な問題解答付き：https://www.passtest.jp/ISTQB/CT-AI-shiken.html

[2026年11月11日] CT-AI PDF問題とテストエンジンには162問があります [Q73-Q93]

ISTQB CT-AI 認定試験の出題範囲：

コメントを残すコメントをキャンセル

CT-AI練習テスト

関連認証

最近の投稿

アーカイブ

カテゴリー

[2026年11月11日] CT-AI PDF問題とテストエンジンには162問があります [Q73-Q93]

ISTQB CT-AI 認定試験の出題範囲：

コメントを残す コメントをキャンセル

CT-AI練習テスト

関連認証

最近の投稿

アーカイブ

カテゴリー

コメントを残すコメントをキャンセル