The 11th Workshop on Principles and Practice of Consistency for Distributed Data (PaPoC) will take place on Monday, April 22, 2024, in conjunction with EuroSys 2024.


PaPoC 2024 is a successor to previous workshops in this series (PaPoC 2014, PaPoC 2015, PaPoC 2016, PaPoC 2017, PaPoC 2018, PaPoC 2019, PaPoC 2020, PaPoC 2021, PaPoC 2022, and PaPoC 2023) which brought together researchers and practitioners in the areas of distributed systems, programming languages, databases, and concurrent programming.

The PaPoC workshop investigates the trade-offs among different consistency models for distributed systems, and their operational characteristics. While stronger consistency models can be easier for programmers to reason about, weaker consistency models can often provide better availability and performance. Beyond the well-known tension between Consistency, Availability, and Partition-tolerance, as captured by the CAP theorem, many nuanced consistency models and algorithms have been developed for different purposes. Distributed consistency models are needed in large-scale datacenter-based systems, but also in edge networks with wide geographic distribution, and even in end-user applications running on mobile devices with intermittent network connectivity. It is clear that there is no universally best solution for sharing data in these different settings.

In order to address these challenges, the PaPoC workshop brings together theoreticians and practitioners from different horizons: system development, distributed algorithms, concurrency, fault tolerance, databases, programming languages and verification, including both academia and industry. Topics of interest include (but are not limited to) models and mechanisms for consistency in distributed systems, including replicated data types/CRDTs, causal consistency, transaction isolation levels, hybrid consistency models such as RedBlue consistency, analysis of program correctness with regard to different consistency models, formal verification of consistency properties, and studies of performance, scalability, and programmability.