A semantically rich approach for collaborative model edition

Michaux, Jonathan; Blanc, Xavier; Shapiro, Marc; Sutra, Pierre

doi:10.1145/1982185.1982500

Cited by 12 publications

(3 citation statements)

References 7 publications

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“…In particular, a large class of ORS, e.g., Bayou [23], CPraxis [18], IceCube [16], Telex [2], use speculative executions, i.e., operations are tentatively applied as they are received from the user or from the other sites. In such systems, the sites may receive the operations in different orders and thus, they may have to repeatedly roll-back some operations as they gradually converge towards a final order (for example, in the case of Bayou, the final order is decided by a designated primary site).…”

Section: Introductionmentioning

confidence: 99%

Verifying eventual consistency of optimistic replication systems

Bouajjani

Enea

Hamza

2014

Proceedings of the 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages

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We address the verification problem of eventual consistency of optimistic replication systems. Such systems are typically used to implement distributed data structures over large scale networks. We introduce a formal definition of eventual consistency that applies to a wide class of existing implementations, including the ones using speculative executions. Then, we reduce the problem of checking eventual consistency to reachability and model checking problems. This reduction enables the use of existing verification tools for message-passing programs in the context of verifying optimistic replication systems. Furthermore, we derive from these reductions decision procedures for checking eventual consistency of systems implemented as finite-state programs communicating through unbounded unordered channels.

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Section: Introductionmentioning

confidence: 99%

Verifying eventual consistency of optimistic replication systems

Bouajjani

Enea

Hamza

2014

Proceedings of the 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages

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“…Operation-based model representation [32] has been proposed for reasoning about streams of model operations. The C-Praxis approach [35] defines six CRUD model operations and defines how these operations interact. The CRDTs of lowkey are geared towards the more complex semantics of graphs and, thus, they provide a superset of these operations.…”

Section: Conflict-free Replicated Data Typesmentioning

confidence: 99%

Real-time Collaborative Multi-Level Modeling by Conflict-Free Replicated Data Types

Dávid¹,

Syriani²

2022

Preprint

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The need for real-time collaborative solutions in model-driven engineering has been increasing over the past years. Conflict-free replicated data types (CRDT) provide scalable and robust replication mechanisms that align well with the requirements of real-time collaborative environments. In this paper, we propose a real-time collaborative multi-level modeling framework to support advanced modeling scenarios, built on a collection of custom CRDTs, specifically tailored for the needs of modeling environments. We demonstrate the benefits of the framework through an illustrative modeling case and compare it with other state-of-the-art modeling frameworks.

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“…The variant called simply causal consistency (abbreviated as CC) allows non-causally depen-dent operations to be executed in different orders by different sites, and decisions about these orders to be revised by each site. This models mechanisms for solving the conflict between non-causally dependent operations where each site speculates on an order between such operations and possibly roll-backs some of them if needed later in the execution, e.g., [6,27,34,39]. We also consider two stronger notions, namely causal memory (CM) [2,35], and causal convergence (CCv) [11,12,35].…”

Section: Introductionmentioning

confidence: 99%

On verifying causal consistency

BouajjaniAhmed¹,

EneaConstantin²,

GuerraouiRachid³

et al. 2017

SIGPLAN Not.

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Abstract. Causal consistency is one of the most adopted consistency criteria for distributed implementations of data structures. It ensures that operations are executed at all sites according to their causal precedence. We address the issue of verifying automatically whether the executions of an implementation of a data structure are causally consistent. We consider two problems: (1) checking whether one single execution is causally consistent, which is relevant for developing testing and bug finding algorithms, and (2) verifying whether all the executions of an implementation are causally consistent.We show that the first problem is NP-complete. This holds even for the read-write memory abstraction, which is a building block of many modern distributed systems. Indeed, such systems often store data in key-value stores, which are instances of the readwrite memory abstraction. Moreover, we prove that, surprisingly, the second problem is undecidable, and again this holds even for the read-write memory abstraction. However, we show that for the read-write memory abstraction, these negative results can be circumvented if the implementations are data independent, i.e., their behaviors do not depend on the data values that are written or read at each moment, which is a realistic assumption.We prove that for data independent implementations, the problem of checking the correctness of a single execution w.r.t. the read-write memory abstraction is polynomial time. Furthermore, we show that for such implementations the set of non-causally consistent executions can be represented by means of a finite number of register automata. Using these machines as observers (in parallel with the implementation) allows to reduce polynomially the problem of checking causal consistency to a state reachability problem. This reduction holds regardless of the class of programs used for the implementation, of the number of read-write variables, and of the used data domain. It allows leveraging existing techniques for assertion/reachability checking to causal consistency verification. Moreover, for a significant class of implementations, we derive from this reduction the decidability of verifying causal consistency w.r.t. the read-write memory abstraction.

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A semantically rich approach for collaborative model edition

Cited by 12 publications

References 7 publications

Verifying eventual consistency of optimistic replication systems

Verifying eventual consistency of optimistic replication systems

Real-time Collaborative Multi-Level Modeling by Conflict-Free Replicated Data Types

On verifying causal consistency

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