标题： Codetations：程序和其他文档的智能、持久笔记和界面 显示英文标题

标题： Codetations: Intelligent, Persistent Notes and UIs for Programs and Other Documents

摘要： 软件开发者在其所编写的代码及其上下文中维持着广泛的思维模型，常常依赖记忆来检索或重构设计决策、边界情况以及调试经验。 这些缺失的环节和数据不仅妨碍了开发者，而且最近也阻碍了与不熟悉代码的大规模语言模型（LLMs）的工作。 我们提出了Codetations系统，该系统帮助开发者通过丰富的笔记和工具来上下文化文档。 与先前的方法不同，Codetations中的笔记位于文档之外以避免代码混乱，采用混合编辑跟踪/基于LLM的方法附着到文档中的片段上。 它们的内容是动态的、交互式的，并且与代码更改同步。 一个工作示例表明，带有交互式收集的数据的相关笔记在代码修复期间提高了LLM的性能。 在我们的用户评估中，开发者称赞了这些特性，并看到了我们用LLM在几分钟内生成的注释类型的巨大潜力。 显示英文摘要

摘要： Software developers maintain extensive mental models of code they produce and its context, often relying on memory to retrieve or reconstruct design decisions, edge cases, and debugging experiences. These missing links and data obstruct both developers and, more recently, large language models (LLMs) working with unfamiliar code. We present Codetations, a system that helps developers contextualize documents with rich notes and tools. Unlike previous approaches, notes in Codetations stay outside the document to prevent code clutter, attaching to spans in the document using a hybrid edit-tracking/LLM-based method. Their content is dynamic, interactive, and synchronized with code changes. A worked example shows that relevant notes with interactively-collected data improve LLM performance during code repair. In our user evaluation, developers praised these properties and saw significant potential in annotation types that we generated with an LLM in just a few minutes.