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In computing, reactive programming is a declarative programming paradigm concerned with data streams and the propagation of change. With this paradigm, it is possible to express static (e.g., arrays) or dynamic (e.g., event emitters) data streams with ease, and also communicate that an inferred dependency within the associated execution model exists, which facilitates the automatic propagation ...
The original formulation of functional reactive programming can be found in the ICFP 97 paper Functional Reactive Animation by Conal Elliott and Paul Hudak. [1] FRP has taken many forms since its introduction in 1997. One axis of diversity is discrete vs. continuous semantics. Another axis is how FRP systems can be changed dynamically. [2]
A synchronous programming language is a computer programming language optimized for programming reactive systems. Computer systems can be sorted in three main classes: Transformational systems take some inputs, process them, deliver their outputs, and terminate their execution. A typical example is a compiler.
Rule-based programming – a network of rules of thumb that comprise a knowledge base and can be used for expert systems and problem deduction & resolution; Visual programming – manipulating program elements graphically rather than by specifying them textually (e.g. Simulink); also termed diagrammatic programming [1]
ReactiveX (Rx, also known as Reactive Extensions) is a software library originally created by Microsoft that allows imperative programming languages to operate on sequences of data regardless of whether the data is synchronous or asynchronous. It provides a set of sequence operators that operate on each item in the sequence.
Reactive Streams were proposed to become part of Java 9 by Doug Lea, leader of JSR 166 [8] as a new Flow class [9] that would include the interfaces currently provided by Reactive Streams. [5] [10] After a successful 1.0 release of Reactive Streams and growing adoption, the proposal was accepted and Reactive Streams was included in JDK9 via the ...
In computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views streams, or sequences of events in time, as the central input and output objects of computation.
In computer science, futures, promises, delays, and deferreds are constructs used for synchronizing program execution in some concurrent programming languages.Each is an object that acts as a proxy for a result that is initially unknown, usually because the computation of its value is not yet complete.