{"title":"运行时异常自动检测的分层行为模型","authors":"Xiaomin Wan, Xiaoguang Mao","doi":"10.1109/ANTHOLOGY.2013.6784956","DOIUrl":null,"url":null,"abstract":"In order to detect runtime errors using program monitoring, specifications are necessary. This paper presents a novel model that describes hierarchical structure of program runtime behavior. The model is composed of elements with granularities from activity, object to action. By observing program behavior as it runs, we construct hierarchical view of program executions and extract behavioral models automatically. After that, we propose an automatic technique for runtime error detection for java programs with a preliminary experiment.","PeriodicalId":203169,"journal":{"name":"IEEE Conference Anthology","volume":"169 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hierarchical behavioral model for automatic runtime anomaly detection\",\"authors\":\"Xiaomin Wan, Xiaoguang Mao\",\"doi\":\"10.1109/ANTHOLOGY.2013.6784956\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to detect runtime errors using program monitoring, specifications are necessary. This paper presents a novel model that describes hierarchical structure of program runtime behavior. The model is composed of elements with granularities from activity, object to action. By observing program behavior as it runs, we construct hierarchical view of program executions and extract behavioral models automatically. After that, we propose an automatic technique for runtime error detection for java programs with a preliminary experiment.\",\"PeriodicalId\":203169,\"journal\":{\"name\":\"IEEE Conference Anthology\",\"volume\":\"169 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Conference Anthology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANTHOLOGY.2013.6784956\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Conference Anthology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANTHOLOGY.2013.6784956","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hierarchical behavioral model for automatic runtime anomaly detection
In order to detect runtime errors using program monitoring, specifications are necessary. This paper presents a novel model that describes hierarchical structure of program runtime behavior. The model is composed of elements with granularities from activity, object to action. By observing program behavior as it runs, we construct hierarchical view of program executions and extract behavioral models automatically. After that, we propose an automatic technique for runtime error detection for java programs with a preliminary experiment.