Distributed applications are traditionally developed as separate modules, often in different
languages, which react to events, like user input, and in turn produce new events for the …

Reactive programming over a network is a challenging task because efficient elimination of
temporary violations of data flow invariants, known as glitches, in a distributed setting is still …

The reactive programming paradigm aims to simplify the development of reactive systems. It
provides abstractions to define time-changing values that are automatically updated by the …

Fully peer-to-peer application software promises many benefits over cloud software, in
particular, being able to function indefinitely without requiring servers. Research on …

Ubiquitous connectivity of web, mobile, and IoT computing platforms has fostered a variety of
distributed applications with decentralized state. These applications execute across multiple …

Local-first software manages and processes private data locally while still enabling
collaboration between multiple parties connected via partially unreliable networks. Such …

The execution of an application written in a reactive language involves transfer of data and
control flow between imperative and reactive abstractions at well-defined points. In a multi …

Abstract Function-as-a-Service (FaaS, serverless) computing systems use an actor-like
model that executes a function asynchronously, atomically and in an isolated context …

Signals are principal abstraction in reactive programming languages and constitute the
basics of reactive computations in modern systems, such as the Internet of Things. Signals …

A signal in reactive programming (RP) is a function of time whose value is updated
automatically without performing explicit re-assignments. SignalJ, a Java-based RP …