Monadic Functional Reactive Programming

Functional Reactive Programming (FRP) is a way to program reactive systems in functional style, eliminating many of the problems that arise from imperative techniques. In this paper, we present an alternative FRP formulation that is based on the notion of a reactive computation: a monadic computation which may require the occurrence of external events to continue. A signal computation is a reactive computation that may also emit values. In contrast to signals in other FRP formulations, signal computations can end, leading to a monadic interface for sequencing signal phases. This interface has several advantages: routing is implicit, sequencing signal phases is easier and more intuitive than when using the switching combinators found in other FRP approaches, and dynamic lists require much less boilerplate code. In other FRP approaches, either the entire FRP expression is re-evaluated on each external stimulus, or impure techniques are used to prevent redundant re-computations. We show how Monadic FRP can be implemented straightforwardly in a purely functional way while preventing redundant re-computations

Monadic functional reactive programming

Functional Reactive Programming (FRP) is a way to program reactive systems in functional style, eliminating many of the problems that arise from imperative techniques. In this paper, we present an alternative FRP formulation that is based on the notion of a reactive computation: a monadic computation which may require the occurrence of external events to continue. A signal computation is a reactive computation that may also emit values. In contrast to signals in other FRP formulations, signal computations can end, leading to a monadic interface for sequencing signal phases. This interface has several advantages: routing is implicit, sequencing signal phases is easier and more intuitive than when using the switching combinators found in other FRP approaches, and dynamic lists require much less boilerplate code. In other FRP approaches, either the entire FRP expression is re-evaluated on each external stimulus, or impure techniques are used to prevent redundant re-computations. We show how Monadic FRP can be implemented straightforwardly in a purely functional way while preventing redundant re-computations