{"title":"验证软件度量:产生质量鉴别器","authors":"N. Schneidewind","doi":"10.1109/ISSRE.1991.145385","DOIUrl":null,"url":null,"abstract":"The author proposes a comprehensive metrics validation methodology that has six validation criteria, each of which supports certain quality functions. New criteria are defined and illustrated, including consistency, discrimination power, tracking, and repeatability. He shows that certain nonparametric statistical methods like contingency tables play an important role in evaluating metrics against the validity criteria. A detailed example emphasizing the discriminative power validity criterion is presented.<<ETX>>","PeriodicalId":338844,"journal":{"name":"Proceedings. 1991 International Symposium on Software Reliability Engineering","volume":"325 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Validating software metrics: producing quality discriminators\",\"authors\":\"N. Schneidewind\",\"doi\":\"10.1109/ISSRE.1991.145385\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The author proposes a comprehensive metrics validation methodology that has six validation criteria, each of which supports certain quality functions. New criteria are defined and illustrated, including consistency, discrimination power, tracking, and repeatability. He shows that certain nonparametric statistical methods like contingency tables play an important role in evaluating metrics against the validity criteria. A detailed example emphasizing the discriminative power validity criterion is presented.<<ETX>>\",\"PeriodicalId\":338844,\"journal\":{\"name\":\"Proceedings. 1991 International Symposium on Software Reliability Engineering\",\"volume\":\"325 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 1991 International Symposium on Software Reliability Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSRE.1991.145385\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 1991 International Symposium on Software Reliability Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSRE.1991.145385","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The author proposes a comprehensive metrics validation methodology that has six validation criteria, each of which supports certain quality functions. New criteria are defined and illustrated, including consistency, discrimination power, tracking, and repeatability. He shows that certain nonparametric statistical methods like contingency tables play an important role in evaluating metrics against the validity criteria. A detailed example emphasizing the discriminative power validity criterion is presented.<>