An Image Processing Language: External and Shallow/Deep Embeddings

Robert J. Stewart
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引用次数: 3

Abstract

Programming language users demand high performance, easy to understand syntax, and tooling such as profilers, debuggers and integrated development environments. Historically they were standalone, each with its own lexer and parser to implement a syntax, and an interpreter or compiler to implement a semantics. This approach incurs substantial engineering costs, both for the initial construction and also for ongoing maintenance as a language and its standard library grows. Modern language technology enables a more cost effective approach, namely to embed new languages inside existing languages, inheriting a host language's tooling, and its community as potential users. This paper uses a small image processing language to compare shallow and deep language embeddings with the external language approach. It focuses on optimisation opportunities, performance, ease of use and engineering costs.
一种图像处理语言:外部和浅/深嵌入
编程语言用户需要高性能、易于理解的语法,以及诸如分析器、调试器和集成开发环境之类的工具。历史上它们是独立的,每个都有自己的词法分析器和解析器来实现语法,以及解释器或编译器来实现语义。这种方法会产生大量的工程成本,包括最初的构建和随着语言及其标准库的增长而进行的维护。现代语言技术支持一种更经济有效的方法,即在现有语言中嵌入新语言,继承宿主语言的工具,并将其社区作为潜在用户。本文采用一种小型图像处理语言与外部语言方法对浅语言和深语言嵌入进行比较。它侧重于优化机会、性能、易用性和工程成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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