{"title":"识别并发事件组件中事件之间的因果关系","authors":"M. Dias, D. Richardson","doi":"10.1109/ASE.2002.1115021","DOIUrl":null,"url":null,"abstract":"Concurrent event-based components present characteristics that impose difficulties in understanding their dynamic behavior, mainly for interpreting the cause and effect relations between input and output events in component interactions. In this paper, we propose a technique to help in the process of understanding the dynamic behavior of concurrent event-based components. It checks the event trace (generated by monitoring the component execution) against a specification of the component communication protocol (even with a possibly incomplete or incorrect specification). The technique identifies and presents the more probable cause and effect relations between the component events, providing also a measurement related to this probability.","PeriodicalId":163532,"journal":{"name":"Proceedings 17th IEEE International Conference on Automated Software Engineering,","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Identifying cause and effect relations between events in concurrent event-based components\",\"authors\":\"M. Dias, D. Richardson\",\"doi\":\"10.1109/ASE.2002.1115021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Concurrent event-based components present characteristics that impose difficulties in understanding their dynamic behavior, mainly for interpreting the cause and effect relations between input and output events in component interactions. In this paper, we propose a technique to help in the process of understanding the dynamic behavior of concurrent event-based components. It checks the event trace (generated by monitoring the component execution) against a specification of the component communication protocol (even with a possibly incomplete or incorrect specification). The technique identifies and presents the more probable cause and effect relations between the component events, providing also a measurement related to this probability.\",\"PeriodicalId\":163532,\"journal\":{\"name\":\"Proceedings 17th IEEE International Conference on Automated Software Engineering,\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 17th IEEE International Conference on Automated Software Engineering,\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASE.2002.1115021\",\"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 17th IEEE International Conference on Automated Software Engineering,","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASE.2002.1115021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identifying cause and effect relations between events in concurrent event-based components
Concurrent event-based components present characteristics that impose difficulties in understanding their dynamic behavior, mainly for interpreting the cause and effect relations between input and output events in component interactions. In this paper, we propose a technique to help in the process of understanding the dynamic behavior of concurrent event-based components. It checks the event trace (generated by monitoring the component execution) against a specification of the component communication protocol (even with a possibly incomplete or incorrect specification). The technique identifies and presents the more probable cause and effect relations between the component events, providing also a measurement related to this probability.