因果一致性的静态序列化性分析

Lucas Brutschy, Dimitar Dimitrov, Peter Müller, Martin T. Vechev
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引用次数: 27

摘要

许多分布式数据库只提供弱一致性保证,以减少同步开销并在网络分区下保持可用。然而,这会导致在更强的保证下不可能发生的行为。这样的行为很容易违背程序员的直觉,导致难以察觉的错误。在本文中,我们提出了一种静态分析,用于检测运行在因果一致数据库之上的应用程序的不可序列化行为。我们的技术基于一种新颖的局部可序列化性标准,并将数据库文献中基于图的技术的概括与另一种互补的分析技术相结合,该分析技术将我们的可序列化性标准编码为一阶逻辑公式,由SMT求解器进行检查。这种分析更昂贵,但更精确,并产生了具体的反例。我们实现了我们的方法,并在两个不同领域的许多应用程序上进行了评估:云支持的移动应用程序和分布式数据库的客户端。我们的实验表明,我们的分析能够检测到有害的串行性违规,同时只产生少量的假警报。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Static serializability analysis for causal consistency
Many distributed databases provide only weak consistency guarantees to reduce synchronization overhead and remain available under network partitions. However, this leads to behaviors not possible under stronger guarantees. Such behaviors can easily defy programmer intuition and lead to errors that are notoriously hard to detect. In this paper, we propose a static analysis for detecting non-serializable behaviors of applications running on top of causally-consistent databases. Our technique is based on a novel, local serializability criterion and combines a generalization of graph-based techniques from the database literature with another, complementary analysis technique that encodes our serializability criterion into first-order logic formulas to be checked by an SMT solver. This analysis is more expensive yet more precise and produces concrete counter-examples. We implemented our methods and evaluated them on a number of applications from two different domains: cloud-backed mobile applications and clients of a distributed database. Our experiments demonstrate that our analysis is able to detect harmful serializability violations while producing only a small number of false alarms.
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