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  2. Reactive programming - Wikipedia

    en.wikipedia.org/wiki/Reactive_programming

    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 ...

  3. Async/await - Wikipedia

    en.wikipedia.org/wiki/Async/await

    The asynchronous workflows are implemented as CE (computation expressions). They can be defined without specifying any special context (like async in C#). F# asynchronous workflows append a bang (!) to keywords to start asynchronous tasks. The following async function downloads data from an URL using an asynchronous workflow:

  4. Comparison of multi-paradigm programming languages - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_multi...

    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]

  5. ReactiveX - Wikipedia

    en.wikipedia.org/wiki/ReactiveX

    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.

  6. Synchronous programming language - Wikipedia

    en.wikipedia.org/wiki/Synchronous_programming...

    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.

  7. Stream processing - Wikipedia

    en.wikipedia.org/wiki/Stream_processing

    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.

  8. Concurrent computing - Wikipedia

    en.wikipedia.org/wiki/Concurrent_computing

    Cω (C omega)—for research, extends C#, uses asynchronous communication; C#—supports concurrent computing using lock, yield, also since version 5.0 async and await keywords introduced; Clojure—modern, functional dialect of Lisp on the Java platform; Concurrent Clean—functional programming, similar to Haskell

  9. Synchronous learning - Wikipedia

    en.wikipedia.org/wiki/Synchronous_learning

    A lecture is an example of synchronous learning in a face-to-face environment, because learners and teachers are all in the same place at the same time. Another example of a synchronous learning event would involve students watching a live web stream of a class, while simultaneously taking part in a discussion.

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