Alpuente María, Ballis Demis, Escobar Santiago, Galán Pascual Daniel, Sapiña Julia
VRAIN (Valencian Research Institute for Artificial Intelligence), Universitat Politècnica de València, Camino de Vera s/n, 46020 Valencia, Spain.
DMIF, University of Udine, Via delle Scienze, 206, 33100 Udine, Italy.
MethodsX. 2022 Aug 3;9:101802. doi: 10.1016/j.mex.2022.101802. eCollection 2022.
Partial evaluation (PE) is a branch of computer science that achieves code optimization via specialization. This article describes a PE methodology for optimizing rewrite theories that encode concurrent as well as nondeterministic systems by means of the Maude language. The main advantages of the proposed methodology can be summarized as follows:•An automatic program optimization technique for rewrite theories featuring several PE criteria that support the specialization of a broad class of rewrite theories.•An incremental partial evaluation modality that allows the key specialization components to be encapsulated at the desired granularity level to facilitate progressive refinements of the specialization.•All executability theory requirements are preserved by the PE transformation. Also the transformation ensures the semantic equivalence between the original rewrite theory and the specialized theory under rather mild conditions.
部分求值(PE)是计算机科学的一个分支,它通过特化实现代码优化。本文描述了一种部分求值方法,用于优化通过Maude语言编码并发以及非确定性系统的重写理论。所提出方法的主要优点可总结如下:
一种针对重写理论的自动程序优化技术,具有多个部分求值标准,支持对广泛类别的重写理论进行特化。
一种增量式部分求值模式,允许将关键特化组件封装在所需的粒度级别,以促进特化的逐步细化。
部分求值转换保留了所有可执行性理论要求。此外,该转换在相当温和的条件下确保原始重写理论与特化理论之间的语义等价。