发表机构
University of Calgary; University of Hawaii at Manoa; UFRPE Federal University of Pernambuco（卡尔加里大学; 夏威夷大学马诺阿分校; 伯南布哥联邦大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出Tether 2.0，一个基于LLM的助手，通过工作流导向交互支持ADHD软件工程师，在规划、编码、调试和审查中提供结构化模式与持久记忆，经专家反馈和实际使用验证，能促进任务进展和中断后恢复。
AI 中文摘要
软件工程工作流程通常并非为满足患有注意力缺陷多动障碍（ADHD）的开发者的需求而设计，尽管已知他们在任务启动、持续注意力和任务完成方面面临挑战。与此同时，大型语言模型（LLMs）正日益集成到编程工具中，但现有系统并未考虑神经多样性，也不支持开发任务中的结构化进展。在本工作中，我们提出了Tether 2.0，一个基于LLM的助手，旨在通过跨规划、编码、调试和审查的工作流导向交互来支持患有ADHD的软件工程师。该工具命名为Tether 2.0，因为它基于原始Tether系统的开源代码和基础构建。我们的方法结合了结构化交互模式、活动感知上下文和持久记忆，以支持任务进展和连续性。我们通过专家反馈和与一名患有ADHD的软件工程师的实际使用来评估该系统。我们的结果表明，Tether 2.0支持需求澄清、任务分解、增量实现、调试和完成，同时使用户能够在中断后保持进展并恢复工作。这些发现表明，当设计具有工作流结构和上下文感知交互时，基于LLM的助手可以支持软件开发中的方向、持续进展和学习。
英文摘要
Software engineering workflows are often not designed to accommodate the needs of developers with Attention Deficit Hyperactivity Disorder (ADHD), despite known challenges related to task initiation, sustained attention, and completion. At the same time, large language models (LLMs) are increasingly integrated into programming tools, but existing systems do not account for neurodiversity or support structured progression across development tasks. In this work, we present Tether 2.0, an LLM based assistant designed to support software engineers with ADHD through workflow oriented interaction across planning, coding, debugging, and review. The tool was named Tether 2.0 because it builds upon the open source code and foundations of the original Tether system. Our approach combines structured interaction modes, activity aware context, and persistent memory to support task progression and continuity. We evaluate the system through expert feedback and hands on use with a software engineer with ADHD. Our results indicate that Tether 2.0 supports requirement clarification, task decomposition, incremental implementation, debugging, and completion, while enabling users to maintain progress and resume work after interruptions. These findings suggest that LLM based assistants can support direction, sustained progress, and learning in software development when designed with workflow structure and context aware interaction.
