For Open Source Software (OSS) projects, discussions in Issue Tracking Systems (ITS) serve as a crucial collaboration mechanism for diverse stakeholders. However, these discussions can become lengthy and entangled, making it hard to find relevant information and make further contributions. In this work, we study the use of summarization to aid users in collaboratively making sense of OSS issue discussion threads. We reveal a complex picture of how summarization is used by issue users in practice as a strategy to help develop and manage their discussions. Grounded on the different objectives served by the summaries and the outcome of our formative study with OSS stakeholders, we identified a set of guidelines to inform the design of collaborative summarization tools for OSS issue discussions. We then developed SUMMIT, a tool that allows issue users to collectively construct summaries of different types of information discussed, as well as a set of comments representing continuous conversations within the thread. To alleviate the manual effort involved, SUMMIT uses techniques that automatically detect information types and summarize texts to facilitate the generation of these summaries. A lab user study indicates that, as the users of SUMMIT, OSS stakeholders adopted different strategies to acquire information on issue threads. Furthermore, different features of SUMMIT effectively lowered the perceived difficulty of locating information from issue threads and enabled the users to prioritize their effort. Overall, our findings demonstrated the potential of SUMMIT, and the corresponding design guidelines, in supporting users to acquire information from lengthy discussions in ITSs. Our work sheds light on key design considerations and features when exploring crowd-based and machine-learning-enabled instruments for asynchronous collaboration on complex tasks such as OSS development.

翻译：对于开源软件项目而言，问题跟踪系统中的讨论是多元利益相关者进行协同的关键机制。然而，这些讨论可能变得冗长且纠缠不清，导致难以查找相关信息并进行后续贡献。本研究探讨了如何利用摘要技术帮助用户协同理解开源软件问题讨论线程。我们揭示了问题用户在实践中将摘要作为策略性工具来发展和管理讨论的复杂图景。基于摘要所服务的不同目标及与开源软件利益相关者进行形成性研究的结果，我们提出了一套指导性准则，用于设计面向开源软件问题讨论的协同摘要工具。随后开发了SUMMIT工具，该工具允许问题用户共同构建涉及不同类型信息的摘要，以及代表线程内持续对话的评论集合。为减轻人工负担，SUMMIT采用自动检测信息类型和文本摘要的技术来辅助生成这些摘要。实验室用户研究表明，作为SUMMIT的使用者，开源软件利益相关者采用了不同策略获取问题线程中的信息。此外，SUMMIT的差异化功能有效降低了从问题线程中定位信息的感知难度，使用户能够优先分配精力。总体而言，我们的发现验证了SUMMIT及其对应设计准则在支持用户从ITS冗长讨论中获取信息方面的潜力。本研究揭示了在复杂任务（如开源软件开发）的异步协作中，基于众包和机器学习工具的关键设计考量与功能特征。