一句话：提出开源模块化透明数据收集的 JetBrains 代码补全插件，支持可复现人机交互研究。
AI 代码补全工具在软件开发中广泛使用，但其用户交互数据多被大公司私有，学术界难以开展可复现的人机交互研究与大规模数据分析。本文提出 Code4Me V2，一个面向研究、开源、基于客户端-服务器架构的 JetBrains IDE 代码补全插件，提供内联代码补全和上下文感知聊天助手。其核心贡献是模块化且透明的数据收集框架，使研究者能细粒度控制遥测与上下文采集。评估结合专家评估和八名参与者的用户研究；代码补全性能与工业界相当，平均延迟 200ms，反馈表明工具具有信息性和实用性。
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 Code4Me V2, a research-oriented, open-source code completion plugin for JetBrains IDEs, as a solution to this limitation. Code4Me V2 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. Code4Me V2 achieves industry-comparable performance in terms of code completion, with an average latency of 200ms. 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 on https://app.code4me.me.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@inproceedings{abs-2510-03755,
title = {Code4MeV2: a Research-oriented Code-completion Platform},
author = {Roham Koohestani and Parham Bateni and Aydin Ebrahimi and Behdad Etezadi and Kiarash Karimi and Maliheh Izadi},
booktitle = {ICSE},
year = {2026},
doi = {10.1145/3774748.3787616}
}