A Framework for Transactional Consistency Models with Atomic Visibility

Cerone, Andrea; Bernardi, Giovanni; Gotsman, Alexey

doi:10.4230/lipics.concur.2015.58

Cited by 22 publications

(20 citation statements)

References 23 publications

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“…For example, early works by Fekete et al [2005] and Jorwekar et al [2007] proposed lightweight syntactic analyses to check for serializability anomalies in centralized databases, by looking for dangerous structures in the over-approximated static graph of all possible dynamic dependency conflicts. Several recent works [Bernardi and Gotsman 2016;Cerone et al 2015;Cerone and Gotsman 2016;Cerone et al 2017;Warszawski and Bailis 2017; have continued along this line, by deriving different types of problematic structures in dependency graphs that are possible under different weak consistency mechanisms, and then checking for these structures on static dependency graphs.…”

Section: Related Workmentioning

confidence: 99%

CLOTHO: directed test generation for weakly consistent database systems

Rahmani

Nagar

Delaware

et al. 2019

Proc. ACM Program. Lang.

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Relational database applications are notoriously difficult to test and debug. Concurrent execution of database transactions may violate complex structural invariants that constraint how changes to the contents of one (shared) table affect the contents of another. Simplifying the underlying concurrency model is one way to ameliorate the difficulty of understanding how concurrent accesses and updates can affect database state with respect to these sophisticated properties. Enforcing serializable execution of all transactions achieves this simplification, but it comes at a significant price in performance, especially at scale, where database state is often replicated to improve latency and availability.To address these challenges, this paper presents a novel testing framework for detecting serializability violations in (SQL) database-backed Java applications executing on weakly-consistent storage systems. We manifest our approach in a tool named clotho, that combines a static analyzer and a model checker to generate abstract executions, discover serializability violations in these executions, and translate them back into concrete test inputs suitable for deployment in a test environment. To the best of our knowledge, clotho is the first automated test generation facility for identifying serializability anomalies of Java applications intended to operate in geo-replicated distributed environments. An experimental evaluation on a set of industry-standard benchmarks demonstrates the utility of our approach.

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Section: Related Workmentioning

confidence: 99%

CLOTHO: directed test generation for weakly consistent database systems

Rahmani

Nagar

Delaware

et al. 2019

Proc. ACM Program. Lang.

View full text Add to dashboard Cite

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“…A function op : Event → Op determines the operation a given event denotes. We follow the specification framework in [7,8].…”

Section: Snapshot Isolationmentioning

confidence: 99%

“…A consistency model specification is a set of consistency axioms Φ constraining abstract executions. The model allows those histories for which there exists an abstract execution that satisfies the axioms: We first briefly explain the consistency axioms that are necessary for defining (Adya) snapshot isolation, namely Int, Ext, Prefix, and NoConflict [7,8]. In Section 2.3, we will introduce a few new consistency axioms and formally define several variants of snapshot isolation using them.…”

Section: Consistency Axiomsmentioning

confidence: 99%

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Verifying Transactional Consistency of MongoDB

Ouyang¹,

Wei²,

Huang³

et al. 2021

Preprint

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MongoDB is a popular general-purpose, document-oriented, distributed NoSQL database. It supports transactions in three different deployments: single-document transactions utilizing the WiredTiger storage engine in a standalone node, multi-document transactions in a replica set which consists of a primary node and several secondary nodes, and distributed transactions in a sharded cluster which is a group of multiple replica sets, among which data is sharded. A natural and fundamental question about Mon-goDB transactions is: What transactional consistency guarantee do MongoDB Transactions in each deployment provide? However, it lacks both concise pseudocode of MongoDB transactions in each deployment and formal specification of the consistency guarantees which MongoDB claimed to provide. In this work, we formally specify and verify the transactional consistency protocols of MongoDB. Specifically, we provide a concise pseudocode for the transactional consistency protocols in each MongoDB deployment, namely WiredTiger, ReplicaSet, and ShardedCluster, based on the official documents and source code. We then prove that WiredTiger, ReplicaSet, and ShardedCluster satisfy different variants of snapshot isolation, namely StrongSI, RealtimeSI, and SessionSI, respectively. We also propose and evaluate efficient white-box checking algorithms for MongoDB transaction protocols against their consistency guarantees, effectively circumventing the NP-hard obstacle in theory.

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“…There have been several directions of work addressing the correctness of database-backed applications. We directly build upon one line of work concerned with the logical formalization of isolation levels [Adya et al 2000;Berenson et al 1995;Biswas and Enea 2019;Cerone et al 2015;X3 1992]. Our work relies on the axiomatic definitions of isolation levels, as given in [Biswas and Enea 2019], which also investigated the problem of checking whether a given history satisfies a certain isolation level.…”

Section: Related Workmentioning

confidence: 99%

MonkeyDB: Effectively Testing Correctness against Weak Isolation Levels

Biswas¹,

Kakwani²,

Vedurada³

et al. 2021

Preprint

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Modern applications, such as social networking systems and e-commerce platforms are centered around using large-scale storage systems for storing and retrieving data. In the presence of concurrent accesses, these storage systems trade off isolation for performance. The weaker the isolation level, the more behaviors a storage system is allowed to exhibit and it is up to the developer to ensure that their application can tolerate those behaviors. However, these weak behaviors only occur rarely in practice, that too outside the control of the application, making it difficult for developers to test the robustness of their code against weak isolation levels.This paper presents MonkeyDB, a mock storage system for testing storage-backed applications. MonkeyDB supports a Key-Value interface as well as SQL queries under multiple isolation levels. It uses a logical specification of the isolation level to compute, on a read operation, the set of all possible return values. MonkeyDB then returns a value randomly from this set. We show that MonkeyDB provides good coverage of weak behaviors, which is complete in the limit. We test a variety of applications for assertions that fail only under weak isolation. MonkeyDB is able to break each of those assertions in a small number of attempts.CCS Concepts: • Software and its engineering → Software testing and debugging;

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A Framework for Transactional Consistency Models with Atomic Visibility

Cited by 22 publications

References 23 publications

CLOTHO: directed test generation for weakly consistent database systems

CLOTHO: directed test generation for weakly consistent database systems

Verifying Transactional Consistency of MongoDB

MonkeyDB: Effectively Testing Correctness against Weak Isolation Levels

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