Beware of the Interactions of Variability Layers When Reasoning about Evolution of MongoDB

Luc Lesoil, M. Acher, Arnaud Blouin, J. Jézéquel
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Abstract

With commits and releases, hundreds of tests are run on varying conditions (e.g., over different hardware and workload) that can help to understand evolution and ensure non-regression of software performance. We hypothesize that performance is not only sensitive to evolution of software, but also to different variability layers of its execution environment, spanning the hardware, the operating system, the build, or the workload processed by the software. Leveraging the MongoDB dataset, our results show that changes in hardware and workload can drastically impact performance evolution and thus should be taken into account when reasoning about performance. An open problem resulting from this study is how to manage the variability layers in order to efficiently test the performance evolution of a software.
在推理MongoDB的演化时,要注意可变性层之间的相互作用
通过提交和发布,数百个测试在不同的条件下运行(例如,在不同的硬件和工作负载上),这有助于理解演变并确保软件性能的非回归。我们假设性能不仅对软件的发展敏感,而且对其执行环境的不同可变性层敏感,包括硬件、操作系统、构建或软件处理的工作负载。利用MongoDB数据集,我们的结果表明硬件和工作负载的变化会极大地影响性能演变,因此在推理性能时应该考虑到这一点。该研究带来的一个开放性问题是如何管理可变性层,以便有效地测试软件的性能演变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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