云系统配置设计与实现的演化研究
An Evolutionary Study of Configuration Design and Implementation in Cloud Systems
摘要：
提出了许多技术来检测云系统中的软件错误配置和诊断由这种错误配置引起的非预期行为。检测和诊断是朝着正确方向迈出的一步：错误配置会导致许多代价高昂的故障和严重的性能问题。但是，我们认为，继续关注检测和诊断是一个更严重的问题的症状：配置设计和实现还不是一流的软件工程在云系统中的努力。关于开发人员如何以及为什么发展配置设计和实现，以及他们在这样做时面临的挑战，我们知之甚少。本文提出了一个源代码级的云系统中的配置设计和实现的演变研究。我们的目标是了解修改初始配置设计/实现决策的基本原理和开发人员实践，特别是在响应错误配置的后果时。为此，我们研究了1178个与配置相关的提交，这些提交来自四个大规模、主动维护的开源云系统（HDFS、HBase、Spark和Cassandra）的2.5年版本控制历史。我们得到新的见解的软件配置工程过程。我们的研究结果激励新的技术，通过改进云系统中的配置设计和实施过程，主动减少错误配置。我们强调了一些未来的研究方向。
英文摘要：
Many techniques were proposed for detecting software misconfigurations in cloud systems and for diagnosing unintended behavior caused by such misconfigurations. Detection and diagnosis are steps in the right direction: misconfigurations cause many costly failures and severe performance issues. But, we argue that continued focus on detection and diagnosis is symptomatic of a more serious problem: configuration design and implementation are not yet first-class software engineering endeavors in cloud systems. Little is known about how and why developers evolve configuration design and implementation, and the challenges that they face in doing so. This paper presents a source-code level study of the evolution of configuration design and implementation in cloud systems. Our goal is to understand the rationale and developer practices for revising initial configuration design/implementation decisions, especially in response to consequences of misconfigurations. To this end, we studied 1178 configuration-related commits from a 2.5 year version-control history of four large-scale, actively-maintained open-source cloud systems (HDFS, HBase, Spark, and Cassandra). We derive new insights into the software configuration engineering process. Our results motivate new techniques for proactively reducing misconfigurations by improving the configuration design and implementation process in cloud systems. We highlight a number of future research directions.
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