Functional reactive programming, continued
Henrik Nilsson, Antony Courtney, John Peterson
Abstract
Henrik Nilsson, Antony Courtney, John Peterson
Abstract
Functional Reactive Programming (FRP) extends a host programming language with a notion of time flow. Arrowized FRP (AFRP) is a version of FRP embedded in Haskell based on the arrow combinators. AFRP is a powerful synchronous dataflow programming language with hybrid modeling capabilities, combining advanced synchronous dataflow features with the higher-order lazy functional abstractions of Haskell. In this paper, we describe the AFRP programming style and our Haskell-based implementation. Of particular interest are the AFRP combinators that support dynamic collections and continuation-based switching. We show how these combinators can be used to express systems with an evolving structure that are difficult to model in more traditional dataflow languages.
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Functional Reactive Programming (FRP) extends a host programming language with a notion of time flow. Arrowized FRP (AFRP) is a version of FRP embedded in Haskell based on the arrow combinators. AFRP is a powerful synchronous dataflow programming language with hybrid modeling capabilities, combining advanced synchronous dataflow features with the higher-order lazy functional abstractions of Haskell. In this paper, we describe the AFRP programming style and our Haskell-based implementation. Of particular interest are the AFRP combinators that support dynamic collections and continuation-based switching. We show how these combinators can be used to express systems with an evolving structure that are difficult to model in more traditional dataflow languages.
Key concepts: Dataflow, Haskell, Computer science, Combinatory logic, Programming language, Functional programming, Functional reactive programming, Programming paradigm