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copied!<p>OK, from background knowledge and from reading the Wikipedia page to which you pointed, it appears that reactive programming is something like dataflow computing but with specific external "stimuli" triggering a set of nodes to fire and perform their computations.</p> <p>This is pretty well suited to UI design, for example, in which touching a user interface control (say, the volume control on a music playing application) might need to update various display items and the actual volume of audio output. When you modify the volume (a slider, let's say) that would correspond to modifying the value associated with a node in a directed graph.</p> <p>Various nodes having edges from that "volume value" node would automatically be triggered and any necessary computations and updates would naturally ripple through the application. The application "reacts" to the user stimulus. Functional reactive programming would just be the implementation of this idea in a functional language, or generally within a functional programming paradigm.</p> <p>For more on "dataflow computing", search for those two words on Wikipedia or using your favorite search engine. The general idea is this: the program is a directed graph of nodes, each performing some simple computation. These nodes are connected to each other by graph links that provide the outputs of some nodes to the inputs of others.</p> <p>When a node fires or performs its calculation, the nodes connected to its outputs have their corresponding inputs "triggered" or "marked". Any node having all inputs triggered/marked/available automatically fires. The graph might be implicit or explicit depending on exactly how reactive programming is implemented.</p> <p>Nodes can be looked at as firing in parallel, but often they are executed serially or with limited parallelism (for example, there may be a few threads executing them). A famous example was the <a href="https://pdfs.semanticscholar.org/a81e/ccf02dc85e08fb34212ae56842366fe38678.pdf" rel="noreferrer">Manchester Dataflow Machine</a>, which (IIRC) used a tagged data architecture to schedule execution of nodes in the graph through one or more execution units. Dataflow computing is fairly well suited to situations in which triggering computations asynchronously giving rise to cascades of computations works better than trying to have execution be governed by a clock (or clocks).</p> <p>Reactive programming imports this "cascade of execution" idea and seems to think of the program in a dataflow-like fashion but with the proviso that some of the nodes are hooked to the "outside world" and the cascades of execution are triggered when these sensory-like nodes change. Program execution would then look like something analogous to a complex reflex arc. The program may or may not be basically sessile between stimuli or may settle into a basically sessile state between stimuli.</p> <p>"non-reactive" programming would be programming with a very different view of the flow of execution and relationship to external inputs. It's likely to be somewhat subjective, since people will likely be tempted to say anything that responds to external inputs "reacts" to them. But looking at the spirit of the thing, a program that polls an event queue at a fixed interval and dispatches any events found to functions (or threads) is less reactive (because it only attends to user input at a fixed interval). Again, it's the spirit of the thing here: one can imagine putting a polling implementation with a fast polling interval into a system at a very low level and program in a reactive fashion on top of it.</p>

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