Active Expressions: Basic Building Blocks for Reactive Programming

Abstract

Modern software development without reactive programming is hard to imagine. Reactive programming favors a wide class of contemporary software systems that respond to user input, network messages, and other events.While reactive programming is an active field of research, the implementation of reactive concepts remains challenging. In particular, change detection represents a hard but inevitable necessity when implementing reactive concepts. Typically, change detection mechanisms are not intended for reuse but are tightly coupled to the particular change resolution mechanism. As a result, developers often have to re-implement similar abstractions. A reusable primitive for change detection is still missing.To find a suitable primitive, we identify commonalities in existing reactive concepts. We discover a class of reactive concepts, state-based reactive concepts. All state-based reactive concepts share a common change detection mechanism: they detect changes in the evaluation result of an expression.On the basis of the identified common change detection mechanism, we propose active expressions as a reusable primitive. By abstracting the tedious implementation details of change detection, active expressions can ease the implementation of reactive programming concepts.We evaluate the design of active expressions by re-implementing a number of existing state-based reactive concepts using them. The resulting implementations highlight the expressiveness of active expressions.Active expressions enable the separation of essential from non-essential parts when reasoning about reactive programming concepts. By using active expressions as a primitive for change detection, developers of reactive language constructs and runtime support can now focus on the design of how application programmers should be able to react to change. Ultimately, we would like active expressions to encourage experiments with novel reactive programming concepts and with that to yield a wider variety of them to explore. ACM CCS

Zone-based Layer Activation

“…We expose four life-cycle callbacks for zones in Dexie.Promise: beforeEnter, beforeLeave, afterEnter, and afterLeave. These callbacks are de ned as zone properties: { beforeEnter ( from , zone ) { /* ... */ } , afterLeave ( zone , to ) { /* ... */ } } 12 https://www.w3.org/TR/IndexedDB/#idl-def-IDBEnvironment accessed on May 1 st 2020 13 https://dexie.org/ accessed on May 1 st 2020 14 https://dexie.org/docs/Promise/Promise.PSD accessed on 21 st April 2020 All callbacks receive two parameters: the zone we change from and the zone we change to. As an example, beforeEnter is invoked right before switching to the zone on which the callback is de ned while the other zone is still active.…”

“…• Extending the integration with asynchronous operations to other meta programming concepts, such as Active Expressions [13] and Babylonian Programming [15,16]. • Applying the concept of replaying behavior adaptations to a more general approach to control, postpone, and resume execution.…”

“…The IndexedDB12 wrapper Dexie13 includes a zonelike utility called Dexie.Promise14 . Dexie allows developers to describe database transactions as a series of asynchronous tasks.…”

Distributed system development with ScalaLoci

“…Rx is available for both Java (RxJava) and JavaScript (RxJS), but as separate implementations, i.e., reactive dependencies cannot cross the boundaries among different hosts. Recently, Ramson and Hirschfeld [2017] proposed active expressions as a primitive for change detection, upon which different kinds of RP can be built. Other recent research directions in RP include debugging [Banken et al 2018;Perez and Nilsson 2017;Salvaneschi and Mezini 2016], thread-safe concurrency [Drechsler et al 2018], and application to new domains such as IoT and edge computing [Calus et al 2017] and autonomous vehicles [Finkbeiner 129:27 et al 2017].…”

On the Semantics of Distributed Reactive Programming: The Cost of Consistency

“…Ramson and Hirschfeld recently proposed Active Expressions [50] as a fundamental primitive to implement different flavours of RP. Other current RP research directions include debugging [51], [52], [53] and application to new domains such as IoT/edge computing and autonomous vehicles [54], [55], [56].…”