Conal Elliott

I submitted a paper Simply efficient functional reactivity to ICFP 2008.

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 efficiency and simplicity, 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”).

I submitted a paper Simply efficient functional reactivity to ICFP 2008. Abstract: Functional reactive programming (FRP) has simple and powerful semantics, but has resisted efficient implementation. In particular, most past...

This post continues from “Reactive values from the future” and “Reactive normal form”.

Fran/FRP reactive behaviors could change continuously, while reactive values change only discretely. The Reactive library keeps continuity orthogonal to reactivity. To combine continuity and reactivity, simply compose reactivity with a non-reactive type of functions of time.

Continue reading ‘Blending continuity into reactive values’ »

This post continues from “Reactive values from the future” and “Reactive normal form”. Fran/FRP reactive behaviors could change continuously, while reactive values change only discretely. The Reactive library keeps continuity...