{"title":"考虑测试剖面和运行剖面的软件可靠性增长模型","authors":"Jing Zhao, Hongwei Liu, G. Cui, Xiaozong Yang","doi":"10.1109/COMPSAC.2005.142","DOIUrl":null,"url":null,"abstract":"The testing and operation environments may be essentially different, thus the fault detection rate (FDR) of testing phase is different from that of the operation phase. In this paper, based on the representative model, G-O model, of nonhomogeneous Poisson process (NHPP), a transformation is performed between the FDR of the testing phase to that of the operation considering the profile differences of the two phases, and then a software reliability growth model (SRGM) called TO-SRGM describing the differences of the FDR between the testing phase and the operation phase is proposed. Finally, the parameters of the model are estimated using the least squares estimate (LSE) based on normalized failure data. Experiment results show that the goodness-of-fit of the TO-SRGM is better than that of the G-0 model and the PZ-SRGM on the normalized failure data set.","PeriodicalId":419267,"journal":{"name":"29th Annual International Computer Software and Applications Conference (COMPSAC'05)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Software reliability growth model considering testing profile and operation profile\",\"authors\":\"Jing Zhao, Hongwei Liu, G. Cui, Xiaozong Yang\",\"doi\":\"10.1109/COMPSAC.2005.142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The testing and operation environments may be essentially different, thus the fault detection rate (FDR) of testing phase is different from that of the operation phase. In this paper, based on the representative model, G-O model, of nonhomogeneous Poisson process (NHPP), a transformation is performed between the FDR of the testing phase to that of the operation considering the profile differences of the two phases, and then a software reliability growth model (SRGM) called TO-SRGM describing the differences of the FDR between the testing phase and the operation phase is proposed. Finally, the parameters of the model are estimated using the least squares estimate (LSE) based on normalized failure data. Experiment results show that the goodness-of-fit of the TO-SRGM is better than that of the G-0 model and the PZ-SRGM on the normalized failure data set.\",\"PeriodicalId\":419267,\"journal\":{\"name\":\"29th Annual International Computer Software and Applications Conference (COMPSAC'05)\",\"volume\":\"91 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"29th Annual International Computer Software and Applications Conference (COMPSAC'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPSAC.2005.142\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"29th Annual International Computer Software and Applications Conference (COMPSAC'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPSAC.2005.142","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Software reliability growth model considering testing profile and operation profile
The testing and operation environments may be essentially different, thus the fault detection rate (FDR) of testing phase is different from that of the operation phase. In this paper, based on the representative model, G-O model, of nonhomogeneous Poisson process (NHPP), a transformation is performed between the FDR of the testing phase to that of the operation considering the profile differences of the two phases, and then a software reliability growth model (SRGM) called TO-SRGM describing the differences of the FDR between the testing phase and the operation phase is proposed. Finally, the parameters of the model are estimated using the least squares estimate (LSE) based on normalized failure data. Experiment results show that the goodness-of-fit of the TO-SRGM is better than that of the G-0 model and the PZ-SRGM on the normalized failure data set.