领域特定语言的有效执行:人口学和细胞生物学两种方法的比较

Till Köster, A. Uhrmacher
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引用次数: 0

摘要

领域特定语言(dsl)提供针对特定问题类进行优化的抽象。在建模和仿真中,领域专家可以使用dsl来使用他们领域中的概念和规则来表达模型。一个挑战是找到执行这些模型的有效方法。在这里,我们将介绍为两个不同的应用程序领域实现两个不同dsl的经验。第一种是ML-Rules,它使用一种外部语言的自定义语法来描述细胞生物系统中的转变,如化学反应。对于第二个版本ML3,我们在Rust编程语言中嵌入了一种内部语言。ML3是为基于agent的仿真而设计的。两种语言都遵循事件驱动的连续时间马尔可夫链语义。然而,在高效执行方面的挑战有所不同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Execution for Domain Specific Languages: Comparing Two Approaches for Demography and Cellular Biology
Domain Specific Languages (DSLs) provide an abstraction optimized for a specific class of problems. In Modelling and Simulation, DSLs can be used by domain experts to express a model using the concepts and rules from their domain. One challenge is to find efficient means of executing these models. Here we present our experience in realizing two different DSLs for two different application domains. The first, ML-Rules, uses a custom syntax of an external language to describe transitions in cell biological systems as chemical reactions. For the second, ML3, we have an internal language embedded in the Rust programming language. ML3 is designed for agent-based simulation. Both languages follow an event-driven Continuous-time Markov chain semantic. However, the challenges in efficient execution differ.
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