标题： 从众人群中获得更好的需求：开源软件中开发人员对功能请求的参与 显示英文标题

标题： Towards Better Requirements from the Crowd: Developer Engagement with Feature Requests in Open Source Software

摘要： 随着用户需求的演变，有效整合功能请求对于保持软件的相关性和用户满意度至关重要。 功能请求通常以自然语言表达，由于沟通差距或请求者有限的技术能力，常常存在歧义或信息不完整的问题。 这些问题可能导致误解、错误实现和软件质量下降。 虽然寻求请求者澄清是一种常见的策略，用于减轻这些风险，但目前尚不清楚开发人员在实践中如何进行这一澄清过程——他们如何提出澄清问题，寻求技术或上下文细节，就目标和用例达成一致，或者在不尝试澄清的情况下决定关闭请求。 本研究调查了功能请求容易出现自然语言缺陷（即模糊或不完整）的情况，以及在开源软件（OSS）开发中的澄清对话动态，旨在了解开发人员如何处理模糊或不完整功能请求。 我们的研究结果表明，发布在OSS平台上的功能请求确实存在模糊和不完整的情况，有时两者同时存在。 我们还发现，针对解决这些缺陷的明确澄清并不常见；开发人员通常更关注与项目目标保持一致，而不是解决模糊的文本。 当发生澄清时，重点在于理解用户意图/目标和可行性，而不是技术细节。 通过描述开源问题跟踪器中的澄清动态，这项工作识别出可以改善用户-开发人员协作的模式，并为有效处理功能请求提供最佳实践指导。 显示英文摘要

摘要： As user demands evolve, effectively incorporating feature requests is crucial for maintaining software relevance and user satisfaction. Feature requests, typically expressed in natural language, often suffer from ambiguity or incomplete information due to communication gaps or the requester's limited technical expertise. These issues can lead to misinterpretation, faulty implementation, and reduced software quality. While seeking clarification from requesters is a common strategy to mitigate these risks, little is known about how developers engage in this clarification process in practice-how they formulate clarifying questions, seek technical or contextual details, align on goals and use cases, or decide to close requests without attempting clarification. This study investigates how feature requests are prone to NL defects (i.e. ambiguous or incomplete) and the conversational dynamics of clarification in open-source software (OSS) development, aiming to understand how developers handle ambiguous or incomplete feature requests. Our findings suggest that feature requests published on the OSS platforms do possess ambiguity and incompleteness, and in some cases, both. We also find that explicit clarification for the resolution of these defects is uncommon; developers usually focus on aligning with project goals rather than resolving unclear text. When clarification occurs, it emphasizes understanding user intent/goal and feasibility, rather than technical details. By characterizing the dynamics of clarification in open-source issue trackers, this work identifies patterns that can improve user-developer collaboration and inform best practices for handling feature requests effectively.