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| Section | Objectives |
|---|---|
| Testing AI-Based Systems Overview | - AI Testing Fundamentals
|
| ML Neural Networks and Testing | - Neural Networks
|
| Using AI for Testing | - AI-Assisted Testing
|
| ML Data | - Data Quality
|
| Methods and Techniques for Testing AI-Based Systems | - Test Design Techniques
|
| Introduction to AI | - AI Fundamentals
|
| Quality Characteristics for AI-Based Systems | - AI-Specific Quality Attributes
|
| Machine Learning | - ML Fundamentals
|
| Testing AI-Specific Quality Characteristics | - Quality Validation
|
| Test Environments for AI-Based Systems | - AI Test Infrastructure
|
| ML Functional Performance Metrics | - Performance Evaluation
|
1. Which ONE of the following is the BEST option to optimize the regression test selection and prevent the regression suite from growing large?
SELECT ONE OPTION
A) Using of a random subset of tests.
B) Using an Al-based tool to optimize the regression test suite by analyzing past test results
C) Automating test scripts using Al-based test automation tools.
D) Identifying suitable tests by looking at the complexity of the test cases.
2. 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) Clustering of similar code modules to predict based on similarity.
B) Using a classification model to predict the presence of a defect by using code quality metrics as the input data.
C) Search of similar code based on natural language processing.
D) Identifying the relationship between developers and the modules developed by them.
3. "AllerEgo" is a product that uses sell-learning to predict the behavior of a pilot under combat situation for a variety of terrains and enemy aircraft formations. Post training the model was exposed to the real- world data and the model was found to bebehaving poorly. A lot of data quality tests had been performed on the data to bring it into a shape fit for training and testing.
Which ONE of the following options is least likely to describes the possible reason for the fall in the performance, especially when considering the self-learning nature of the Al system?
SELECT ONE OPTION
A) The unknown nature and insufficient specification of the operating environment might have caused the poor performance.
B) The difficulty of defining criteria for improvement before the model can be accepted.
C) The fast pace of change did not allow sufficient time for testing.
D) There was an algorithmic bias in the Al system.
4. Which ONE of the following options does NOT describe a challenge for acquiring test data in ML systems?
SELECT ONE OPTION
A) Test data being sourced from public sources.
B) Data for the use case is being generated at a fast pace.
C) Compliance needs require proper care to be taken of input personal data.
D) Nature of data constantly changes with lime.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: B | Question # 4 Answer: B |
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