Research on Development of Distributed Software Defect Prediction Model Based on Deep Learning
Software development is becoming increasingly diverse and complex,and in this process,distributed systems have been widely applied.But,the complexity of distributed systems also brings about the problem of high defect rates,which puts higher demands on software quality maintenance.This article discusses in detail the development of a distributed software defect prediction model based on deep learning,including model design,data preprocessing and feature extraction methods,model training,and performance evaluation.This study aims to improve the efficiency and accuracy of defect detection in distributed software development,providing an effective technical support and solution for the field of software engineering.
万方数据
维普
