Software Defect Prediction Using Machine Learning Techniques

Abstract

Software defect prediction provides development groups with observable outcomes while contributing to industrial results and development faults predicting defective code areas can help developers identify bugs and organize their test activities. The percentage of classification providing the proper prediction is essential for early identification. Moreover, software- defected data sets are supported and at least partially recognized due to their enormous dimension.