Software microbenchmarking in the cloud. How bad is it really?
作者: Christoph LaaberJoel ScheunerPhilipp Leitner
作者单位: 1Department of Informatics, University of Zurich
2Software Engineering Division, Chalmers | University of Gothenburg
刊名: Empirical Software Engineering, 2019, Vol.24 (4), pp.2469-2508
来源数据库: Springer Nature Journal
DOI: 10.1007/s10664-019-09681-1
关键词: Performance testingMicrobenchmarkingCloudPerformance-regression detection
英文摘要: Abstract(#br)Rigorous performance engineering traditionally assumes measuring on bare-metal environments to control for as many confounding factors as possible. Unfortunately, some researchers and practitioners might not have access, knowledge, or funds to operate dedicated performance-testing hardware, making public clouds an attractive alternative. However, shared public cloud environments are inherently unpredictable in terms of the system performance they provide. In this study, we explore the effects of cloud environments on the variability of performance test results and to what extent slowdowns can still be reliably detected even in a public cloud. We focus on software microbenchmarks as an example of performance tests and execute extensive experiments on three different well-known...
全文获取路径: Springer Nature  (合作)
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影响因子:1.18 (2012)

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