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ISQI CT-AI_v1.0_World Exam Syllabus Topics:

ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:

1. 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

A) Identifying the relationship between developers and the modules developed by them.
B) Clustering of similar code modules to predict based on similarity.
C) Using a classification model to predict the presence of a defect by using code quality metrics as the input data.
D) Search of similar code based on natural language processing.

2. Written requirements are given in text documents, which ONE of the following options is the BEST way to generate test cases from these requirements?
SELECT ONE OPTION

A) Natural language processing on textual requirements
B) Machine learning on logs of execution
C) GUI analysis by computer vision
D) Analyzing source code for generating test cases

3. The activation value output for a neuron in a neural network is obtained by applying computation to the neuron.
Which ONE of the following options BEST describes the inputs used to compute the activation value?
SELECT ONE OPTION

A) Individual bias at the neuron level, activation values of neurons in the previous layer, and weights assigned to the connections between the neurons.
B) Individual bias at the neuron level, and weights assigned to the connections between theneurons.
C) Individual bias at the neuron level, and activation values of neurons in the previous layer.
D) Activation values of neurons in the previous layer, and weights assigned to the connections between the neurons.

4. Which ONE of the following statements is a CORRECT adversarial example in the context of machine learning systems that are working on image classifiers.
SELECT ONE OPTION

A) These attacks can't be prevented by retraining the model with these examples augmented tothe training data.
B) These attack examples cause a model to predict the correct class with slightly less accuracy even though they look like the original image.
C) Black box attacks based on adversarial examples create an exact duplicate model of the original.
D) These examples are model specific and are not likely to cause another model trained on same task to fail.

Solutions: