{"title":"Industrial Case Study on Supporting the Comprehension of System Behaviour under Load","authors":"Mark D. Syer, Bram Adams, A. Hassan","doi":"10.1109/ICPC.2011.38","DOIUrl":null,"url":null,"abstract":"Large-scale software systems achieve concurrency on enormous scales using a number of different design patterns. Many of these design patterns are based on pools of pre-existing and reusable threads that facilitate incoming service requests. Thread pools limit thread lifecycle overhead (thread creation and destruction) and resource thrashing (thread proliferation). Despite their potential for scalability, thread pools are hard to configure and test because of concurrency risks like synchronization errors and dead lock, and thread pool-specific risks like resource thrashing and thread leakage. Addressing these challenges requires a thorough understanding of the behaviour of the threads in the thread pool. We argue for a methodology to automatically identify and rank deviations in the behaviour of threads based on resource usage.","PeriodicalId":345601,"journal":{"name":"2011 IEEE 19th International Conference on Program Comprehension","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 19th International Conference on Program Comprehension","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPC.2011.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Large-scale software systems achieve concurrency on enormous scales using a number of different design patterns. Many of these design patterns are based on pools of pre-existing and reusable threads that facilitate incoming service requests. Thread pools limit thread lifecycle overhead (thread creation and destruction) and resource thrashing (thread proliferation). Despite their potential for scalability, thread pools are hard to configure and test because of concurrency risks like synchronization errors and dead lock, and thread pool-specific risks like resource thrashing and thread leakage. Addressing these challenges requires a thorough understanding of the behaviour of the threads in the thread pool. We argue for a methodology to automatically identify and rank deviations in the behaviour of threads based on resource usage.