Editing Dataflow (section)

==Software architecture==
[[Dataflow programming|Dataflow computing]] is a software paradigm based on the idea of representing computations as a [[directed graph]], where nodes are computations and data flow along the edges.<ref name="sig">{{cite web |last1=Schwarzkopf |first1=Malte |title=The Remarkable Utility of Dataflow Computing |url=https://www.sigops.org/2020/the-remarkable-utility-of-dataflow-computing/ |website=ACM SIGOPS |access-date=31 July 2022 |date=7 March 2020}}</ref> Dataflow can also be called [[stream processing]] or [[reactive programming]].<ref>[http://www.jonathanbeard.io/blog/2015/09/19/streaming-and-dataflow.html A Short Intro to Stream Processing]</ref>

There have been multiple data-flow/stream processing languages of various forms (see [[Stream processing]]). Data-flow hardware (see [[Dataflow architecture]]) is an alternative to the classic [[von Neumann architecture]]. The most obvious example of data-flow programming is the subset known as [[reactive programming]] with spreadsheets. As a user enters new values, they are instantly transmitted to the next logical "actor" or formula for calculation.

[[Distributed data flow]]s have also been proposed as a programming abstraction that captures the dynamics of distributed multi-protocols. The data-centric perspective characteristic of data flow programming promotes high-level functional specifications and simplifies formal reasoning about system components.