角色专业化模型（RSM）：在智能体软件开发中协调基于大语言模型（LLM）的工具——一项探索性案例研究
The Role Specialization Model (RSM): Coordinating LLM-Based Tools in Agentic Software Development - An Exploratory Case Study
AI总结：
本研究通过探索性案例研究提出角色专业化模型（RSM），协调Antigravity、Gemini CLI等三种LLM工具开发Python气候可视化应用，发现明确角色协调可优化开发质量但需配套策略与人工验证。
AI中文摘要：
将大语言模型（LLM）集成到软件开发工作流中催生了被称为智能体软件工程（SE 3.0）的范式，在该范式下，自主智能体在人类监督下管理完整的开发生命周期。本文呈现一项探索性案例研究，其中依据本研究提出的角色分配框架——角色专业化模型（RSM），协调三种基于LLM的工具：Antigravity（搭载Gemini 2.5后端的智能体集成开发环境）、Gemini CLI和Qwen Code（通过Ollama本地执行）。研究由三个研究问题引导：RQ1，如何通过RSM在实际开发工作流中协调具有不同能力的基于LLM的工具；RQ2，RSM执行过程中会出现哪些偏离计划角色分配的情况，以及解释这些情况的因素是什么；RQ3，生成的产品与ISO/IEC 25010质量模型相比表现如何。研究目标是通过增量开发用于交互式气候数据可视化的Python桌面应用程序来提出RSM。本文记录了工作流、观察到的偏离情况、提示强化技术以及定性质量评估。结果表明，明确的角色协调可支持开发周期组织和架构质量，但需要审慎的协调策略、上下文管理以及对智能体生成输出的人工验证。
英文摘要：
The integration of large language models (LLMs) into software development workflows has given rise to a paradigm known as Agentic Software Engineering (SE 3.0), in which autonomous agents manage full development life cycles under human supervision. This paper presents an exploratory case study in which three LLM-based tools, Antigravity (an agentic IDE with a Gemini 2.5 backend), Gemini CLI, and Qwen Code (local execution via Ollama), are coordinated according to a role-distribution framework proposed in this work as the Role Specialization Model (RSM). Three research questions guide the study: (RQ1) how can LLM-based tools with distinct capabilities be coordinated through the RSM in a real development workflow; (RQ2) what deviations from the planned role distribution emerge during RSM execution and what factors explain them; and (RQ3) how does the resulting product compare against the ISO/IEC 25010 quality model. The objective was to propose the RSM with the incremental development of a Python desktop application for interactive climate-data visualization. The workflow, observed deviations, prompt-hardening techniques, and a qualitative quality assessment are documented. Results suggest that explicit role coordination can support development cycle organization and architectural quality, but requires deliberate coordination strategies, context management, and human verification of agent-generated outputs.
