Developing and reasoning about systems using eventually consistent data stores is a difficult challenge due to the presence of unexpected behaviors that do not occur under sequential consistency. A fundamental problem in this setting is to identify a correctness criterion that precisely captures intended application behaviors yet is generic enough to be applicable to a wide range of applications.

In this paper, we present such a criterion. More precisely, we generalize conflict serializability to the setting of eventual consistency. Our generalization is based on a novel dependency model that incorporates two powerful algebraic properties: commutativity and absorption. These properties enable precise reasoning about programs that employ high-level replicated data types, common in modern systems. To apply our criterion in practice, we also developed a dynamic analysis algorithm and a tool that checks whether a given program execution is serializable.

We performed a thorough experimental evaluation on two real-world use cases: debugging cloud-backed mobile applications and implementing clients of a popular eventually consistent key-value store. Our experimental results indicate that our criterion reveals harmful synchronization problems in applications, is more effective at finding them than prior approaches, and can be used for the development of practical, eventually consistent applications.