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Machine Learning based Software Testing: Towards a Classification Framework Mahdi Noorian1, Ibrahim Bagheri1,2, and Whacking Du1 University of New Brunswick, Fredericton, Canada1 Athabasca University,

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What is machine learning-based software testing?

Machine learning-based software testing involves using machine learning algorithms and techniques to automate and improve the software testing process by predicting defects, identifying patterns, and optimizing testing strategies.

Who is required to file machine learning-based software testing?

Companies or organizations that develop or use machine learning-based software testing tools are required to file machine learning-based software testing.

How to fill out machine learning-based software testing?

Machine learning-based software testing can be filled out by documenting the testing methodology, results, and any relevant data used in the process.

What is the purpose of machine learning-based software testing?

The purpose of machine learning-based software testing is to improve the efficiency and effectiveness of software testing by leveraging machine learning capabilities to identify defects and optimize testing procedures.

What information must be reported on machine learning-based software testing?

Information such as the testing plan, results, data sets used, and any relevant metrics or analysis must be reported on machine learning-based software testing.

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