开源代码补全工具，支持研究数据采集与分析
Code4MeV2: a Research-oriented Code-completion Platform
- 基于客户端-服务器架构，支持实时补全与上下文对话
- 平均延迟200毫秒，性能媲美工业级产品
- 专为学术研究设计，可精细控制数据收集
AI驱动的代码补全工具在软件开发中广泛应用，但其用户交互数据多被大型企业私有化，阻碍了学术界的研究。为此，本文提出Code4MeV2，一个面向研究的开源代码补全插件，兼容JetBrains IDEs。该系统采用客户端-服务器架构，提供行内补全与上下文感知聊天助手。核心贡献在于模块化、透明的数据收集框架，使研究者可精细控制遥测与上下文信息获取。Code4MeV2在代码补全性能上达到行业水平，平均延迟为200~毫秒。通过专家评估和8名用户的使用研究，反馈表明其信息丰富且实用。欢迎社区使用并贡献。更多信息见https://app.code4me.me。
原文摘要 · Abstract (English)
The adoption of AI-powered code completion tools in software development has increased substantially, yet the user interaction data produced by these systems remain proprietary within large corporations. This creates a barrier for the academic community, as researchers must often develop dedicated platforms to conduct studies on human--AI interaction, making reproducible research and large-scale data analysis impractical. In this work, we introduce Code4MeV2, a research-oriented, open-source code completion plugin for JetBrains IDEs, as a solution to this limitation. Code4MeV2 is designed using a client--server architecture and features inline code completion and a context-aware chat assistant. Its core contribution is a modular and transparent data collection framework that gives researchers fine-grained control over telemetry and context gathering. Code4MeV2 achieves industry-comparable performance in terms of code completion, with an average latency of 200~ms. We assess our tool through a combination of an expert evaluation and a user study with eight participants. Feedback from both researchers and daily users highlights its informativeness and usefulness. We invite the community to adopt and contribute to this tool. More information about the tool can be found at https://app.code4me.me.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。