{"title":"将执行日志抽象为企业应用程序的执行事件(短文)","authors":"Z. Jiang, A. Hassan, P. Flora, Gilbert Hamann","doi":"10.1109/QSIC.2008.50","DOIUrl":null,"url":null,"abstract":"Monitoring the execution of large enterprise systems is needed to ensure that such complex systems are performing as expected. However, common techniques for monitoring, such as code instrumentation and profiling have significant performance overhead, and require access to the source code and to system experts. In this paper, we propose using execution logs to monitor the execution of applications. Unfortunately, execution logs are not designed for monitoring purposes. Each occurrence of an execution event results in a different log line, since a log line contains dynamic information which varies for each occurrence of the event. We propose an approach which abstracts log lines to a set of execution events. Our approach can handle log lines without having strict requirements on the format of a log line. Through a case study on a large enterprise application, we demonstrate that our approach performs well when abstracting execution logs for large enterprise applications. We compare our approach against the SLCT tool which is commonly used to find line patterns in logs.","PeriodicalId":6446,"journal":{"name":"2008 The Eighth International Conference on Quality Software","volume":"76 6 1","pages":"181-186"},"PeriodicalIF":0.0000,"publicationDate":"2008-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"86","resultStr":"{\"title\":\"Abstracting Execution Logs to Execution Events for Enterprise Applications (Short Paper)\",\"authors\":\"Z. Jiang, A. Hassan, P. Flora, Gilbert Hamann\",\"doi\":\"10.1109/QSIC.2008.50\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Monitoring the execution of large enterprise systems is needed to ensure that such complex systems are performing as expected. However, common techniques for monitoring, such as code instrumentation and profiling have significant performance overhead, and require access to the source code and to system experts. In this paper, we propose using execution logs to monitor the execution of applications. Unfortunately, execution logs are not designed for monitoring purposes. Each occurrence of an execution event results in a different log line, since a log line contains dynamic information which varies for each occurrence of the event. We propose an approach which abstracts log lines to a set of execution events. Our approach can handle log lines without having strict requirements on the format of a log line. Through a case study on a large enterprise application, we demonstrate that our approach performs well when abstracting execution logs for large enterprise applications. We compare our approach against the SLCT tool which is commonly used to find line patterns in logs.\",\"PeriodicalId\":6446,\"journal\":{\"name\":\"2008 The Eighth International Conference on Quality Software\",\"volume\":\"76 6 1\",\"pages\":\"181-186\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"86\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 The Eighth International Conference on Quality Software\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QSIC.2008.50\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 The Eighth International Conference on Quality Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QSIC.2008.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Abstracting Execution Logs to Execution Events for Enterprise Applications (Short Paper)
Monitoring the execution of large enterprise systems is needed to ensure that such complex systems are performing as expected. However, common techniques for monitoring, such as code instrumentation and profiling have significant performance overhead, and require access to the source code and to system experts. In this paper, we propose using execution logs to monitor the execution of applications. Unfortunately, execution logs are not designed for monitoring purposes. Each occurrence of an execution event results in a different log line, since a log line contains dynamic information which varies for each occurrence of the event. We propose an approach which abstracts log lines to a set of execution events. Our approach can handle log lines without having strict requirements on the format of a log line. Through a case study on a large enterprise application, we demonstrate that our approach performs well when abstracting execution logs for large enterprise applications. We compare our approach against the SLCT tool which is commonly used to find line patterns in logs.