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Software Testing Defect Prediction Model by esatjournals is a document available to read on EtoBox.
This document summarizes a research paper that developed a statistical model to predict software defects using historical project data. The model uses multiple linear regression to predict defects based on five parameters: the total number of test cases executed, test team size, allocated development effort, test case execution effort, and total number of components delivered. The model was trained on data from 20 previous software releases. It achieved a high R-squared value of 0.91 and standard error of 5
- Author
- esatjournals
- Language
- EN