{"title":"一种计算超几何软件可靠性模型最大似然估计的快速算法","authors":"Frank Padberg","doi":"10.1109/APAQS.2001.990000","DOIUrl":null,"url":null,"abstract":"We present a fast and exact algorithm to compute maximum likelihood estimates for the number of faults initially contained in a software, using the hypergeometric software reliability model. The algorithm is based on a rigorous mathematical analysis of the growth behavior of the likelihood function for the model. We also clarify the stochastic process underlying the model and prove a recursion formula which is central for most previous work on the hypergeometric software reliability model.","PeriodicalId":145151,"journal":{"name":"Proceedings Second Asia-Pacific Conference on Quality Software","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A fast algorithm to compute maximum likelihood estimates for the hypergeometric software reliability model\",\"authors\":\"Frank Padberg\",\"doi\":\"10.1109/APAQS.2001.990000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a fast and exact algorithm to compute maximum likelihood estimates for the number of faults initially contained in a software, using the hypergeometric software reliability model. The algorithm is based on a rigorous mathematical analysis of the growth behavior of the likelihood function for the model. We also clarify the stochastic process underlying the model and prove a recursion formula which is central for most previous work on the hypergeometric software reliability model.\",\"PeriodicalId\":145151,\"journal\":{\"name\":\"Proceedings Second Asia-Pacific Conference on Quality Software\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Second Asia-Pacific Conference on Quality Software\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APAQS.2001.990000\",\"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 Second Asia-Pacific Conference on Quality Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APAQS.2001.990000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fast algorithm to compute maximum likelihood estimates for the hypergeometric software reliability model
We present a fast and exact algorithm to compute maximum likelihood estimates for the number of faults initially contained in a software, using the hypergeometric software reliability model. The algorithm is based on a rigorous mathematical analysis of the growth behavior of the likelihood function for the model. We also clarify the stochastic process underlying the model and prove a recursion formula which is central for most previous work on the hypergeometric software reliability model.
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