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Inferring Common Language Infrastructure metadata for an ambiguous dynamic language type

机译:以模糊的动态语言类型推断公共语言基础架构元数据

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Dynamic languages play an important role in the computer industry. Most noticeably, a vast majority of web servers and client browsers are running some sort of dynamic language, such as Python, JavaScript or PHP. In light of the ubiquitous attempts to provide a fast and secure environment for dynamic languages, it is imperative to be able to compile them and have them run natively without the necessity for their often-times slow interpretation. Their type system represents one of the most significant differences compared to static languages. The type ambiguity makes it difficult to analyze and run a dynamic program. In this paper, we propose an approach for inferring a single type that combines possible ambiguities on a common language runtime platform. The solution allows for optimized runtime operations and eliminates most of the overhead caused by the need for representing dynamically typed values during runtime.
机译:动态语言在计算机行业中发挥着重要作用。最明显的是,绝大多数Web服务器和客户端浏览器正在运行某种动态语言,例如Python,JavaScript或PHP。鉴于无处不在的尝试为动态语言提供快速安全的环境,必须能够编译它们并使它们自然地运行,而不需要慢慢解释。与静态语言相比,它们的类型系统代表了最显着的差异之一。类型的歧义使得难以分析和运行动态程序。在本文中,我们提出了一种推断出一个类型的方法,该类型将可能的含糊不清在公共语言运行时平台上结合起来。该解决方案允许优化的运行时操作,并消除大部分开销,这是由于在运行时表示动态类型值的需要。

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