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Dataflow programming languages share some features of functional languages, and were generally developed in order to bring some functional concepts to a language more suitable for numeric processing. Some authors use the term datastream instead of dataflow to avoid confusion with dataflow computing or dataflow architecture , based on an ...
Dataflow programming languages rely on a (usually visual) representation of the flow of data to specify the program. Frequently used for reacting to discrete events or for processing streams of data. Examples of dataflow languages include:
Prograph is a visual, object-oriented, dataflow, multiparadigm programming language that uses iconic symbols to represent actions to be taken on data. Commercial Prograph software development environments such as Prograph Classic and Prograph CPX were available for the Apple Macintosh and Windows platforms for many years but were eventually withdrawn from the market in the late 1990s.
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 ...
Dataflow architecture is a dataflow-based computer architecture that directly contrasts the traditional von Neumann architecture or control flow architecture. Dataflow architectures have no program counter, in concept: the executability and execution of instructions is solely determined based on the availability of input arguments to the instructions, [1] so that the order of instruction ...
CAL (the Cal Actor Language) is a high-level programming language [1] for writing actors, which are stateful operators that transform input streams of data objects (tokens) into output streams. CAL has been compiled to a variety of target platforms, including single-core processors, multicore processors, and programmable hardware .
Functional reactive programming (FRP) is a programming paradigm for reactive programming (asynchronous dataflow programming) using the building blocks of functional programming (e.g., map, reduce, filter).
Lucid is a dataflow programming language designed to experiment with non-von Neumann programming models. It was designed by Bill Wadge and Ed Ashcroft and described in the 1985 book Lucid, the Dataflow Programming Language. [1] pLucid was the first interpreter for Lucid.