功能反应型

A. Jeffrey
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引用次数: 14

摘要

函数式响应式编程(FRP)是一种将纯函数语义作为时间索引值的数据流处理的方法。在之前的工作中,我们表明线性时间时间逻辑(LTL)可以用作离散时间FRP的类型系统,并且功能反应性原语执行两个角色:作为构建数据流的组合子,以及作为建设性LTL的证明规则。在本文中,我们增加了第三个角色,通过显示FRP组合子可以用来定义类型流,并且这些功能反应性类型既可以被视为建设性的时间逻辑,也可以被视为功能反应性程序的类型。作为功能反应类型的一个应用,我们证明了过去时间LTL (pLTL)可以用FRP扩展为逻辑pLTL+FRP。该逻辑被表示为布尔表达式流,因此pLTL的有界可满足性可以转化为可满足模理论(SMT)。因此,pLTL+FRP可以作为约束语言用于混合数据属性和时间属性的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Functional reactive types
Functional Reactive Programming (FRP) is an approach to streaming data with a pure functional semantics as time-indexed values. In previous work, we showed that Linear-time Temporal Logic (LTL) can be used as a type system for discrete-time FRP, and that functional reactive primitives perform two roles: as combinators for building streams of data, and as proof rules for constructive LTL. In this paper, we add a third role, by showing that FRP combinators can be used to define streams of types, and that these functional reactive types can be viewed both as a constructive temporal logic, and as the types for functional reactive programs. As an application of functional reactive types, we show that past-time LTL (pLTL) can be extended with FRP to get a logic pLTL+FRP. This logic is expressed as streams of boolean expressions, and so bounded satisfiability of pLTL can be translated to Satisfiability Modulo Theory (SMT). Thus, pLTL+FRP can be used as a constraint language for problems which mix properties of data with temporal properties.
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