VeriFx: Correct Replicated Data Types for the Masses

Distributed systems adopt weak consistency to ensure high availability and low latency, but state convergence is hard to guarantee due to conflicts. Experts carefully design replicated data types (RDTs) that resemble sequential data types and embed conflict resolution mechanisms that ensure convergence. Designing RDTs is challenging as their correctness depends on subtleties such as the ordering of concurrent operations. Currently, researchers manually verify RDTs, either by paper proofs or using proof assistants. Unfortunately, paper proofs are subject to reasoning flaws and mechanized proofs verify a formalization instead of a real-world implementation. Furthermore, writing mechanized proofs is reserved for verification experts and is extremely time-consuming. To simplify the design, implementation, and verification of RDTs, we propose VeriFx, a specialized programming language for RDTs with automated proof capabilities. VeriFx lets programmers implement RDTs atop functional collections and express correctness properties that are verified automatically. Verified RDTs can be transpiled to mainstream languages (currently Scala and JavaScript). VeriFx provides libraries for implementing and verifying Conflict-free Replicated Data Types (CRDTs) and Operational Transformation (OT) functions. These libraries implement the general execution model of those approaches and define their correctness properties. We use the libraries to implement and verify an extensive portfolio of 51 CRDTs, 16 of which are used in industrial databases, and reproduce a study on the correctness of OT functions

VeriFx: Correct Replicated Data Types for the Masses (Artifact)

Our related article presents our novel verification language, called VeriFx. We used VeriFx to implement and verify 51 Conflict-Free Replicated Data Types (CRDTs) and 9 Operational Transformation (OT) functions. This artifact bundles the implementation of the various CRDTs and OT functions described in the article. The artifact also contains a Docker file that can be used to reproduce the verification results (Table 1 and 2 in the article). In addition, the artifact can also be used to run custom VeriFx programs and verify their correctness

ECROs: Building global scale systems from sequential code

Funding Information: We would like to thank Matteo Marra, Jim Bauwens, and the anonymous reviewers for their comments which helped improve the paper. Kevin De Porre is funded by an SB Fellowship of the Research Foundation - Flanders. Project number: 1S98519N. This work was partially supported by Fundação para a Ciência e a Tecnologia - Portugal (FCT/MCTES) under grants UIDB/04516/2020, PTDC/CCI-INF/32081/2017, and LISBOA-01-0145-FEDER-032662/PTDC/CCI-INF/32662/2017.To ease the development of geo-distributed applications, replicated data types (RDTs) offer a familiar programming interface while ensuring state convergence, low latency, and high availability. However, RDTs are still designed exclusively by experts using ad-hoc solutions that are error-prone and result in brittle systems. Recent works statically detect conflicting operations on existing data types and coordinate those at runtime to guarantee convergence and preserve application invariants. However, these approaches are too conservative, imposing coordination on a large number of operations. In this work, we propose a principled approach to design and implement efficient RDTs taking into account application invariants. Developers extend sequential data types with a distributed specification, which together form an RDT. We statically analyze the specification to detect conflicts and unravel their cause. This information is then used at runtime to serialize concurrent operations safely and efficiently. Our approach derives a correct RDT from any sequential data type without changes to the data type's implementation and with minimal coordination. We implement our approach in Scala and develop an extensive portfolio of RDTs. The evaluation shows that our approach provides performance similar to conflict-free replicated data types for commutative operations, and considerably improves the performance of non-commutative operations, compared to existing solutions.publishersversionpublishe

CScript : a distributed programming language for building mixed-consistency applications

Current programming models only provide abstractions for sharing data under a homogeneous consistency model. It is, however, not uncommon for a distributed application to provide strong consistency for one part of the shared data and eventual consistency for another part. Because mixing consistency models is not supported by current programming models, writing such applications is extremely difficult. In this paper we propose CScript, a distributed object-oriented programming language with built-in support for data replication. At its core are consistent and available replicated objects. CScript regulates the interactions between these objects to avoid subtle inconsistencies that arise when mixing consistency models. Our evaluation compares a collaborative text editor built atop CScript with a state-of-the-art implementation. The results show that our approach is flexible and more memory efficient