Push-pull functional reactive programming

Conal Elliott
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引用次数: 138

Abstract

Functional reactive programming (FRP) has simple and powerful semantics, but has resisted efficient implementation. In particular, most past implementations have used demand-driven sampling, which accommodates FRP's continuous time semantics and fits well with the nature of functional programming. Consequently, values are wastefully recomputed even when inputs don't change, and reaction latency can be as high as the sampling period. This paper presents a way to implement FRP that combines data- and demand-driven evaluation, in which values are recomputed only when necessary, and reactions are nearly instantaneous. The implementation is rooted in a new simple formulation of FRP and its semantics and so is easy to understand and reason about. On the road to a new implementation, we'll meet some old friends (monoids, functors, applicative functors, monads, morphisms, and improving values) and make some new friends (functional future values, reactive normal form, and concurrent "unambiguous choice").
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推拉式函数式响应式编程
函数式响应式编程(FRP)具有简单而强大的语义,但难以有效实现。特别是,大多数过去的实现都使用了需求驱动的采样,它适应FRP的连续时间语义,并且很好地符合函数式编程的性质。因此,即使输入没有改变,重新计算值也是浪费的,而且反应延迟可能与采样周期一样高。本文提出了一种实施FRP的方法,该方法结合了数据和需求驱动的评估,其中仅在必要时重新计算值,并且反应几乎是即时的。该实现植根于FRP及其语义的一个新的简单公式,因此易于理解和推理。在通往新实现的道路上,我们会遇到一些老朋友(monoids、函子、应用函子、单子、态态和改进值),并结交一些新朋友(函数未来值、反应范式和并发的“明确选择”)。
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