Study on Software Defect Prediction Model Based on Improved BP Algorithm

Cundong Tang, Li Chen, Zhiping Wang, Y. Sima
{"title":"Study on Software Defect Prediction Model Based on Improved BP Algorithm","authors":"Cundong Tang, Li Chen, Zhiping Wang, Y. Sima","doi":"10.1109/TOCS50858.2020.9339718","DOIUrl":null,"url":null,"abstract":"Software defect is an important indicator to evaluate software product quality. To reduce the defects of software products and to improve the quality of software is always the goal of software development. This paper combines the simulated annealing (SA) algorithm and JCUDA technology to improve the BP algorithm, to build an improved software defect prediction model with higher prediction accuracy. The experimental results show that the software defect prediction model based on improved BP algorithm is able to accurately predict the software defects, which is better than the traditional BP algorithm.","PeriodicalId":373862,"journal":{"name":"2020 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TOCS50858.2020.9339718","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Software defect is an important indicator to evaluate software product quality. To reduce the defects of software products and to improve the quality of software is always the goal of software development. This paper combines the simulated annealing (SA) algorithm and JCUDA technology to improve the BP algorithm, to build an improved software defect prediction model with higher prediction accuracy. The experimental results show that the software defect prediction model based on improved BP algorithm is able to accurately predict the software defects, which is better than the traditional BP algorithm.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于改进BP算法的软件缺陷预测模型研究
软件缺陷是评价软件产品质量的重要指标。减少软件产品的缺陷,提高软件质量一直是软件开发的目标。本文结合模拟退火(SA)算法和JCUDA技术对BP算法进行改进,建立了预测精度更高的改进软件缺陷预测模型。实验结果表明,基于改进BP算法的软件缺陷预测模型能够准确预测软件缺陷,优于传统BP算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Research on Fault Diagnosis Method of Power Grid Based on Artificial Intelligence Research on Digital Oil Painting Based on Digital Image Processing Technology Effect of adding seed nuclei on acoustic agglomeration efficiency of natural fog An overview of biological data generation using generative adversarial networks Application of Intelligent Safety Supervision Based on Artificial Intelligence Technology
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1