Software Fault Prediction Using in Machine Learning

Abstract

A subfield of computer science called software engineering allows for close coordination between system software and customizing it to meet user needs. We have chosen seven unique machine learning algorithms and will put them to the test utilizing the data sets obtained for NASA's public promise repositories. The outcomes of our experiment enable the software's users to identify flaws by choosing the most effective algorithm for completing subsequent tasks, which produces successful outcomes.