{"title":"A coverage based model for software reliability estimation","authors":"P. Jalote, Y.R. Muralidhara","doi":"10.1109/STRQA.1994.526377","DOIUrl":null,"url":null,"abstract":"There is an increasing interest in estimating and predicting the reliability of software systems. Many models exist for reliability estimation. Most of these models consider a software system as a black box and predict the reliability based on the failure data observed during testing. The application of these models require a fair amount of data collection, computation, and expertise and computation for interpreting the results. We propose a model that is based on the coverage history of the program. A software is modeled as a graph, and the reliability of a node is assumed to be a function of the number of times it gets executed during testing-the larger the number of times a node gets executed, the higher its reliability. The reliability of the software system is then computed through simulation by using the reliabilities of the individual nodes. With such a model, coverage analysis tools can easily be extended to compute the reliability also, thereby fully automating reliability estimation.","PeriodicalId":125322,"journal":{"name":"Proceedings of 1994 1st International Conference on Software Testing, Reliability and Quality Assurance (STRQA'94)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1994 1st International Conference on Software Testing, Reliability and Quality Assurance (STRQA'94)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STRQA.1994.526377","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
There is an increasing interest in estimating and predicting the reliability of software systems. Many models exist for reliability estimation. Most of these models consider a software system as a black box and predict the reliability based on the failure data observed during testing. The application of these models require a fair amount of data collection, computation, and expertise and computation for interpreting the results. We propose a model that is based on the coverage history of the program. A software is modeled as a graph, and the reliability of a node is assumed to be a function of the number of times it gets executed during testing-the larger the number of times a node gets executed, the higher its reliability. The reliability of the software system is then computed through simulation by using the reliabilities of the individual nodes. With such a model, coverage analysis tools can easily be extended to compute the reliability also, thereby fully automating reliability estimation.