{"title":"用测试努力对不完美的调试现象建模","authors":"P. K. Kapur, P. S. Grover, S. Younes","doi":"10.1109/ISSRE.1994.341371","DOIUrl":null,"url":null,"abstract":"A software reliability growth model (SRGM) based on non-homogeneous Poisson processes (NHPP) is developed. The model describes the relationship between the calendar time, the testing effort consumption and the error removal process under an imperfect debugging environment. The role of learning (gaining experience) with the progress of the testing phase is taken into consideration by assuming that the imperfect debugging probability is dependent on the current software error content. The model has the in-built flexibility of representing a wide range of growth curves. The model can be used to plan the amount of testing effort required to achieve a pre-determined target in terms of the number of errors removed in a given span of time.<<ETX>>","PeriodicalId":171359,"journal":{"name":"Proceedings of 1994 IEEE International Symposium on Software Reliability Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"Modelling an imperfect debugging phenomenon with testing effort\",\"authors\":\"P. K. Kapur, P. S. Grover, S. Younes\",\"doi\":\"10.1109/ISSRE.1994.341371\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A software reliability growth model (SRGM) based on non-homogeneous Poisson processes (NHPP) is developed. The model describes the relationship between the calendar time, the testing effort consumption and the error removal process under an imperfect debugging environment. The role of learning (gaining experience) with the progress of the testing phase is taken into consideration by assuming that the imperfect debugging probability is dependent on the current software error content. The model has the in-built flexibility of representing a wide range of growth curves. The model can be used to plan the amount of testing effort required to achieve a pre-determined target in terms of the number of errors removed in a given span of time.<<ETX>>\",\"PeriodicalId\":171359,\"journal\":{\"name\":\"Proceedings of 1994 IEEE International Symposium on Software Reliability Engineering\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1994 IEEE International Symposium on Software Reliability Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSRE.1994.341371\",\"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 of 1994 IEEE International Symposium on Software Reliability Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSRE.1994.341371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modelling an imperfect debugging phenomenon with testing effort
A software reliability growth model (SRGM) based on non-homogeneous Poisson processes (NHPP) is developed. The model describes the relationship between the calendar time, the testing effort consumption and the error removal process under an imperfect debugging environment. The role of learning (gaining experience) with the progress of the testing phase is taken into consideration by assuming that the imperfect debugging probability is dependent on the current software error content. The model has the in-built flexibility of representing a wide range of growth curves. The model can be used to plan the amount of testing effort required to achieve a pre-determined target in terms of the number of errors removed in a given span of time.<>