{"title":"一种基于参数评估的软件可靠性预测新方法:航天飞机应用","authors":"N. Schneidewind","doi":"10.1109/SEW.2007.85","DOIUrl":null,"url":null,"abstract":"Software reliability measurement and prediction are used to evaluate model parameters in advance of applying a model. Measurement involves collecting and analyzing data about the observed reliability of software, from which the parameters are estimated, for example, the occurrence of failures during test. Prediction is using a model to forecast future software reliability, for example, time to next failure during operation. In order to demonstrate the prediction methodology, we must use a software reliability model. Since the Schneidewind model has been used on the NASA Shuttle flight software for reliability predictions, and we have a considerable amount of Shuttle failure data, we use the model and data to demonstrate our methodology.","PeriodicalId":277367,"journal":{"name":"31st IEEE Software Engineering Workshop (SEW 2007)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A New Way to Predict Software Reliability with Parameter Evaluation: Shuttle Applications\",\"authors\":\"N. Schneidewind\",\"doi\":\"10.1109/SEW.2007.85\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software reliability measurement and prediction are used to evaluate model parameters in advance of applying a model. Measurement involves collecting and analyzing data about the observed reliability of software, from which the parameters are estimated, for example, the occurrence of failures during test. Prediction is using a model to forecast future software reliability, for example, time to next failure during operation. In order to demonstrate the prediction methodology, we must use a software reliability model. Since the Schneidewind model has been used on the NASA Shuttle flight software for reliability predictions, and we have a considerable amount of Shuttle failure data, we use the model and data to demonstrate our methodology.\",\"PeriodicalId\":277367,\"journal\":{\"name\":\"31st IEEE Software Engineering Workshop (SEW 2007)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"31st IEEE Software Engineering Workshop (SEW 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SEW.2007.85\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"31st IEEE Software Engineering Workshop (SEW 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEW.2007.85","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Way to Predict Software Reliability with Parameter Evaluation: Shuttle Applications
Software reliability measurement and prediction are used to evaluate model parameters in advance of applying a model. Measurement involves collecting and analyzing data about the observed reliability of software, from which the parameters are estimated, for example, the occurrence of failures during test. Prediction is using a model to forecast future software reliability, for example, time to next failure during operation. In order to demonstrate the prediction methodology, we must use a software reliability model. Since the Schneidewind model has been used on the NASA Shuttle flight software for reliability predictions, and we have a considerable amount of Shuttle failure data, we use the model and data to demonstrate our methodology.