Causal commutative arrows revisited
Causal commutative arrows revisited
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重新审视因果交换箭头
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Hai Liu
中科院分区：
文献类型：
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作者：
J. Yallop;Hai Liu
因果交换箭头（CCA）扩展了箭头的额外结构和法律，使它们适合建模领域，如功能反应式编程，微分方程和同步递归。早期的工作已经表明，CCA计算到正常形式的语法转换可以导致显着的性能改善，有时增加程序的速度的数量级。在这项工作中，我们重新制定了规范化为一个类型类实例，并通过流转换器的专门化来获得优化的观察函数，以证明在不离开语言的情况下可以实现相同的显着改进。
Causal commutative arrows (CCA) extend arrows with additional constructs and laws that make them suitable for modelling domains such as functional reactive programming, differential equations and synchronous dataflow. Earlier work has revealed that a syntactic transformation of CCA computations into normal form can result in significant performance improvements, sometimes increasing the speed of programs by orders of magnitude. In this work we reformulate the normalization as a type class instance and derive optimized observation functions via a specialization to stream transformers to demonstrate that the same dramatic improvements can be achieved without leaving the language.