Replicated data types: specification, verification, optimality

Conference item

Geographically distributed systems often rely on replicated eventually consistent data stores to achieve availability and performance. To resolve conflicting updates at different replicas, researchers and practitioners have proposed specialized consistency protocols, called replicated data types, that implement objects such as registers, counters, sets or lists. Reasoning about replicated data types has however not been on par with comparable work on abstract data types and concurrent data types, lacking specifications, correctness proofs, and optimality results.

To fill in this gap, we propose a framework for specifying replicated data types using relations over events and verifying their implementations using replication-aware simulations. We apply it to 7 existing implementations of 4 data types with nontrivial conflictresolution strategies and optimizations (last-writer-wins register, counter, multi-value register and observed-remove set). We also present a novel technique for obtaining lower bounds on the worstcase space overhead of data type implementations and use it to prove optimality of 4 implementations. Finally, we show how to specify consistency of replicated stores with multiple objects axiomatically, in analogy to prior work on weak memory models. Overall, our work provides foundational reasoning tools to support research on replicated eventually consistent stores.

Authors: Burckhardt, S; Gotsman, A; Yang, H; Zawirski, M

• Publication status: Published
• Peer review status: Reviewed (other)
• Publisher: Association for Computing Machinery
• Host title: Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation
• Journal: POPL '14: Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation
• Pages: 271-284
• Publication date: 2014-11-01
• Acceptance date: 2013-10-02
• DOI: 10.1145/2535838.2535848
• ISBN: 9781450325448