{"title":"使用软件科学预测错误数量","authors":"Linda M. Ottenstein","doi":"10.1145/800003.807924","DOIUrl":null,"url":null,"abstract":"An earlier paper presented a model based on software science metrics to give quantitative estimate of the number of bugs in a programming project at the time validation of the project begins. In this paper, we report the results from an attempt to expand the model to estimate the total number of bugs to expect during the total project development. This new hypothesis has been tested using the data currently available in the literature along with data from student projects. The model fits the published data reasonably well, however, the results obtained using the student data are not conclusive.","PeriodicalId":262059,"journal":{"name":"Measurement and evaluation of software quality","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"Predicting numbers of errors using software science\",\"authors\":\"Linda M. Ottenstein\",\"doi\":\"10.1145/800003.807924\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An earlier paper presented a model based on software science metrics to give quantitative estimate of the number of bugs in a programming project at the time validation of the project begins. In this paper, we report the results from an attempt to expand the model to estimate the total number of bugs to expect during the total project development. This new hypothesis has been tested using the data currently available in the literature along with data from student projects. The model fits the published data reasonably well, however, the results obtained using the student data are not conclusive.\",\"PeriodicalId\":262059,\"journal\":{\"name\":\"Measurement and evaluation of software quality\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Measurement and evaluation of software quality\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/800003.807924\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Measurement and evaluation of software quality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/800003.807924","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predicting numbers of errors using software science
An earlier paper presented a model based on software science metrics to give quantitative estimate of the number of bugs in a programming project at the time validation of the project begins. In this paper, we report the results from an attempt to expand the model to estimate the total number of bugs to expect during the total project development. This new hypothesis has been tested using the data currently available in the literature along with data from student projects. The model fits the published data reasonably well, however, the results obtained using the student data are not conclusive.
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