{"title":"感染大小是衡量病毒严重程度的标准","authors":"M. R. Azadmanesh, Matthias Hauswirth","doi":"10.1145/2823363.2823370","DOIUrl":null,"url":null,"abstract":"A simple bug in a program can influence a large part of the program execution by spreading throughout the state at runtime. This is known as program infection. The seriousness of bugs is usually measured by studying their external effects. However, such effects essentially derive from internal factors of a program. Our idea is to focus on internal factors, in particular the infection chain, to measure how serious a bug was. This allows reasoning about bugs from a new and potentially insightful perspective.","PeriodicalId":256833,"journal":{"name":"Proceedings of the 13th International Workshop on Dynamic Analysis","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Infection size as a measure of bug severity\",\"authors\":\"M. R. Azadmanesh, Matthias Hauswirth\",\"doi\":\"10.1145/2823363.2823370\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A simple bug in a program can influence a large part of the program execution by spreading throughout the state at runtime. This is known as program infection. The seriousness of bugs is usually measured by studying their external effects. However, such effects essentially derive from internal factors of a program. Our idea is to focus on internal factors, in particular the infection chain, to measure how serious a bug was. This allows reasoning about bugs from a new and potentially insightful perspective.\",\"PeriodicalId\":256833,\"journal\":{\"name\":\"Proceedings of the 13th International Workshop on Dynamic Analysis\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 13th International Workshop on Dynamic Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2823363.2823370\",\"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 the 13th International Workshop on Dynamic Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2823363.2823370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A simple bug in a program can influence a large part of the program execution by spreading throughout the state at runtime. This is known as program infection. The seriousness of bugs is usually measured by studying their external effects. However, such effects essentially derive from internal factors of a program. Our idea is to focus on internal factors, in particular the infection chain, to measure how serious a bug was. This allows reasoning about bugs from a new and potentially insightful perspective.
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