{"title":"动态软件测试模型","authors":"A. I. Danilov, A. Khomonenko, A. A. Danilov","doi":"10.1109/SCM.2015.7190414","DOIUrl":null,"url":null,"abstract":"Three dynamic process models (strategies) for software testing are offered, which provides the ability to use probabilities of error detection for each module. Labeled graphs, systems of differential equations, probability parameters of test processes and software testing states for these strategies are provided. Results for computational experiments are described.","PeriodicalId":106868,"journal":{"name":"2015 XVIII International Conference on Soft Computing and Measurements (SCM)","volume":"283 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Dynamic software testing models\",\"authors\":\"A. I. Danilov, A. Khomonenko, A. A. Danilov\",\"doi\":\"10.1109/SCM.2015.7190414\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Three dynamic process models (strategies) for software testing are offered, which provides the ability to use probabilities of error detection for each module. Labeled graphs, systems of differential equations, probability parameters of test processes and software testing states for these strategies are provided. Results for computational experiments are described.\",\"PeriodicalId\":106868,\"journal\":{\"name\":\"2015 XVIII International Conference on Soft Computing and Measurements (SCM)\",\"volume\":\"283 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 XVIII International Conference on Soft Computing and Measurements (SCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCM.2015.7190414\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 XVIII International Conference on Soft Computing and Measurements (SCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCM.2015.7190414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Three dynamic process models (strategies) for software testing are offered, which provides the ability to use probabilities of error detection for each module. Labeled graphs, systems of differential equations, probability parameters of test processes and software testing states for these strategies are provided. Results for computational experiments are described.
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