Monitoring refinement via symbolic reasoning

EmmiMichael,; EneaConstantin,; HamzaJad,

doi:10.1145/2813885.2737983

Cited by 5 publications

(2 citation statements)

References 18 publications

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“…Several works have considered the problem of checking strong consistency models such as Linearizability and Sequential consistency (SC) [4,5,11,14,16,17,27,30]. Our recent works [33,31] address the problem of verifying SC and TSO (Total store ordering) gradually by using several variants of causal consistency (and other weak consistency models) including the ones we have considered in this work.…”

Section: Related Workmentioning

confidence: 99%

Checking Causal Consistency of Distributed Databases

et al. 2019

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The CAP Theorem shows that (strong) Consistency, Availability, and Partition tolerance are impossible to be ensured together. Causal consistency is one of the weak consistency models that can be implemented to ensure availability and partition tolerance in distributed systems. In this work, we propose a tool to check automatically the conformance of distributed/concurrent systems executions to causal consistency models. Our approach consists in reducing the problem of checking if an execution is causally consistent to solving Datalog queries. The reduction is based on complete characterizations of the executions violating causal consistency in terms of the existence of cycles in suitably defined relations between the operations occurring in these executions. We have implemented the reduction in a testing tool for distributed databases, and carried out several experiments on real case studies, showing the efficiency of the suggested approach.

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Section: Related Workmentioning

confidence: 99%

Checking Causal Consistency of Distributed Databases

et al. 2019

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“…Based on [12], optimized algorithms were proposed through partial order reduction [13] or compositional reasoning [6]. Model checking was applied for linearizability checking, with simplified first-order formulas that can help improve efficiency [5], [14]. Fine-grained traces were introduced in [8] to accelerate linearizability checking.…”

Section: Pairsnapshotmentioning

confidence: 99%

Localization of Linearizability Faults on the Coarse-grained Level

Zhang¹,

Wu²,

Zhang³

2017

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-Linearizability is an important correctness criterion that guarantees the safety of concurrent data structures. Due to the nondeterminism of concurrent executions, reproduction and localization of a linearizability fault still remain challenging. The existing work mainly focuses on model checking the thread schedule space of a concurrent program on a fine-grained (state) level, and hence suffers from the severe problem of state space explosion. This paper presents a tool called CGVT to build a small test case that is sufficient enough for reproducing a linearizability fault. Given a possibly long history that has been detected non-linearizable, CGVT first locates the operations causing a linearizability violation, and then synthesizes a short test case for further investigation. Moreover, we present several optimization techniques to improve the effectiveness and efficiency of CGVT. We have applied CGVT to 10 concurrent objects, while the linearizability of some of the concurrent objects is unknown yet. The experiments show that CGVT is powerful and efficient enough to build the test cases adaptable for a fine-grained analysis.

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