{"title":"Are the principal components of software complexity data stable across software products?","authors":"T. Khoshgoftaar, D. Lanning","doi":"10.1109/METRIC.1994.344227","DOIUrl":null,"url":null,"abstract":"The current software market is not suitable for organizations that place competitive bids, set schedules, or control projects without regard to past performance. Software quality models based upon data collected from past projects can help engineers to estimate costs of future development efforts, and to control ongoing efforts. Application of principal components analysis can improve the stability and predictive quality of software quality models. However, models based upon principal components are only appropriate for application to products having similar principal components. We apply a statistical technique for quantifying the similarity of principal components. We find that distinct but similar products developed by the same organization can share similar principal components, and that distinct products developed by distinct organizations will likely have dissimilar principal components.<<ETX>>","PeriodicalId":271190,"journal":{"name":"Proceedings of 1994 IEEE 2nd International Software Metrics Symposium","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1994 IEEE 2nd International Software Metrics Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/METRIC.1994.344227","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
The current software market is not suitable for organizations that place competitive bids, set schedules, or control projects without regard to past performance. Software quality models based upon data collected from past projects can help engineers to estimate costs of future development efforts, and to control ongoing efforts. Application of principal components analysis can improve the stability and predictive quality of software quality models. However, models based upon principal components are only appropriate for application to products having similar principal components. We apply a statistical technique for quantifying the similarity of principal components. We find that distinct but similar products developed by the same organization can share similar principal components, and that distinct products developed by distinct organizations will likely have dissimilar principal components.<>
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
