Distributed system replication is widely used as a means of fault-tolerance and scalability.
However, it provides a spectrum of consistency choices that impose a dilemma for clients …

Programming geo-replicated distributed systems is challenging given the complexity of
reasoning about different evolving states on different replicas. Existing approaches to this …

Relational database applications are notoriously difficult to test and debug. Concurrent
execution of database transactions may violate complex structural invariants that constraint …

The replication mechanism resolves some challenges with big data such as data durability,
data access, and fault tolerance. Yet, replication itself gives birth to another challenge known …

Programming efficient distributed, concurrent systems requires new abstractions that go
beyond traditional sequential programming. But programmers already have trouble getting …

Conflict-free replicated data types (CRDTs) aid programmers develop highly available and
scalable distributed systems. However, the literature describes only a limited portfolio of …

We introduce Carol, a refinement-typed programming language for replicated data stores.
The salient feature of Carol is that it allows programming and verifying replicated store …

The CAP theorem states that only two of these properties can be simultaneously guaranteed
in a distributed service:(i) consistency,(ii) availability and (iii) network partition tolerance …

Geo-replication poses an inherent trade-off between low latency, high availability and strong
consistency. While NoSQL databases favor low latency and high availability, relaxing …

In high-throughput, distributed systems, such as large-scale banking infrastructure,
synchronization between actors becomes a bottle-neck in high-contention scenarios. This …