发表机构
Queensland University of Technology（昆士兰科技大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种文学式编程环境，通过语法、解析器、名称图及绑定机制，让代码与相关上下文并置，提升 LLM 窗口利用率，为 LLM 编码智能体提供类 IDE 工具集，并实现了绑定三种编程语言的可运行版本及示例程序。
AI 中文摘要
本文介绍了一种与感知语言的机器智能体协同构建文学式程序的环境。该环境包含可执行程序短文的语法、将名称视为一等对象的解析器、关联 prose（ prose 指程序说明性文本）、名称与可执行构件的内部名称图，以及针对现有语言与测试工具集的绑定机制。这支持将代码与其最相关的自然语言和结构化数据上下文并置，以更好地利用 Large Language Model（LLM，大语言模型）的上下文窗口；还为 LLM 编码智能体提供了更接近面向人类程序员的 Integrated Development Environments（IDE，集成开发环境）中符号感知搜索与使用信息的工具集。我们描述了一个可运行的实现，其绑定了三种已确立的编程语言，并提供了若干示例程序。
英文摘要
This paper introduces an environment for constructing literate programs in concert with language-aware machine agents. This environment includes a grammar for executable program essays, a parser that treats names as first-class objects, an internal name-graph which relates prose, names and executable artifacts, and a binding mechanism for existing languages and testing toolsets. This supports co-location of code with its most relevant natural language and structured data context, making better use of Large Language Model (LLM) context windows. It also provides LLM coding agents with a toolset more analogous to the symbol-aware search and usage information available in human programmer-facing Integrated Development Environments (IDEs). We describe a working implementation with bindings to three established programming languages, and several example programs.
Comments13 pages, 5 figures (code and grammar listings)
