A Comparison Experiment On Software Quality Testing With Machine Learning Using Different Algorithms
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Abstract
The software quality is a particular property that indicates the regular software. The main success factor and departure of software-related organisations in a software project is efficiency. Machine-based standard deviation and mean use of CMMI as a software quality assurance model – which in computer software are structured in terms of objectives, obligations, capacities, tasks, measurement and above all validations via the engineer-based application of ISO 9000/9001-3. Different algorithms such as Random Forest, Decision Tree, Gradient Boosting, Bagging Classifier, Logistic Regression, Bernoulli-NB and CNN are used in this paper to predict software qualities. It contributes to solving and handling a program's time complexity and enhances software efficiency, reliability and security issues
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