让编程像走迷宫，自由探索代码分支的AI助手。
Choose Your Own Adventure: Non-Linear AI-Assisted Programming with EvoGraph
- 用动态图记录代码与AI交互的每一步选择
- 支持对比、合并、回溯不同编程路径
- 适合需要反复试错和反思的开发者
当前AI编程工具多为线性对话式，与编程中常见的迭代和分支特性不符。我们对开发者的初步研究发现，他们常难以探索替代方案、管理提示序列及追踪变更。基于此，我们开发了EvoGraph——一个集成于IDE的插件，将AI互动与代码修改记录为轻量级、可交互的开发图谱。该工具自动保存分支化的AI辅助编码历史，支持用户在图谱中比较、合并、回溯过往的协同编程状态。20名参与者的用户研究显示，EvoGraph有效解决了前期发现的问题，认知负担更低。参与者认为图谱形式有助于安全探索、高效迭代与反思AI生成的改动。本工作揭示了在新兴AI辅助编程环境中，帮助开发者理解并行动于其解题进展的设计机遇。
原文摘要 · Abstract (English)
Current AI-assisted programming tools are predominantly linear and chat-based, which deviates from the iterative and branching nature of programming itself. Our preliminary study with developers using AI assistants suggested that they often struggle to explore alternatives, manage prompting sequences, and trace changes. Informed by these insights, we created EvoGraph, an IDE plugin that integrates AI interactions and code changes as a lightweight and interactive development graph. EvoGraph automatically records a branching AI-assisted coding history and allows developers to manipulate the graph to compare, merge, and revisit prior collaborative AI programming states. Our user study with 20 participants revealed that EvoGraph addressed developers' challenges identified in our preliminary study while imposing lower cognitive load. Participants also found the graph-based representation supported safe exploration, efficient iteration, and reflection on AI-generated changes. Our work highlights design opportunities for tools to help developers make sense of and act on their problem-solving progress in the emerging AI-mediated programming context.
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