Code4MeV2：一個面向研究的代碼補全平台

摘要

在軟件開發領域，採用基於人工智能的代碼補全工具已顯著增加，然而這些系統產生的用戶交互數據仍被大型企業所專有。這為學術界設置了障礙，因為研究人員往往需要開發專用平台來進行人機交互研究，使得可重複研究和大規模數據分析難以實現。本研究中，我們推出了Code4MeV2，這是一款面向研究的開源代碼補全插件，專為JetBrains集成開發環境設計，旨在解決這一限制。Code4MeV2採用客戶端-服務器架構，具備內聯代碼補全和上下文感知聊天助手功能。其核心貢獻在於一個模塊化且透明的數據收集框架，賦予研究人員對遙測和上下文收集的精細控制。Code4MeV2在代碼補全方面達到了與業界相當的性能，平均延遲為200毫秒。我們通過專家評估和八名參與者的用戶研究相結合的方式對工具進行了評估。來自研究人員和日常用戶的反饋均強調了其信息豐富性和實用性。我們誠邀社區採用並為此工具做出貢獻。更多關於該工具的信息，請訪問https://app.code4me.me。

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.

Code4MeV2：一個面向研究的代碼補全平台

Code4MeV2: a Research-oriented Code-completion Platform

摘要

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