SHF: Small: Collaborative Research: Automatically Enhancing Quality of Social Communication Channels to Support Software Developers and Improve Tool Reliability

社交沟通渠道(如Stack Overflow、Slack和GitHub)在软件开发人员的工作效率中扮演着越来越重要的角色，因为开发人员使用这些渠道来协作和协调活动。研究人员已经展示了从这些来源挖掘信息以开发和改进推荐系统、软件集成开发环境和其他工具的额外价值。这些系统的用户抱怨这些渠道上共享的信息质量参差不齐，而且往往很差，尽管有保持质量的内在机制(例如投票、接受的答案)。该项目旨在满足在管理过程中实现自动化的需要，以提高开发人员交流渠道中共享的信息的质量。设想的系统使用多个软件开发人员的社交沟通渠道作为并行证据来源，以确定每个渠道的信息质量。该项目将通过解决三个主要挑战，使开发人员沟通的自动化管理进入实际应用，从而促进最新技术的发展。第一个目标是开发分析，以自动确定和改进开发人员在社交媒体网站上关于质量问题的互动交流的质量，包括软件性能差、过时、矛盾、来源不可靠和重复。第二个目标是探索不同的反馈机制，将高质量的调查结果反馈给社区。第三，该项目将开发针对特定开发人员的环境定制质量测量和反馈的技术。作为项目一部分开发的结果工具、数据集和实验基础设施将被发布，使其他研究人员和实践者能够在项目结果的基础上构建，并最终提高现代软件开发生态系统的质量。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Social communication channels (e.g., Stack Overflow, Slack, and GitHub) play an increasingly important role in software developer productivity, as developers use these channels to collaborate and coordinate activities. Researchers have shown additional value in mining information from these sources to develop and improve recommendation systems, software integrated development environments, and other tools. Users of these systems complain about the varying and often poor quality of the information shared on these channels despite the intrinsic mechanisms for maintaining quality (e.g., voting, accepted answers). This project aims to address the need for automation in curating for increased quality of the information shared in developer communication channels. The envisioned system uses multiple software developers' social communication channels as parallel sources of evidence to establish quality of information in each channel.This project will contribute to the state of the art by tackling three major challenges to bring automated curation of developer communication into practical use. The first aim is to develop analyses for automatically determining and improving the quality of developers' interactive communications on social media sites with regard to quality concerns including poor software properties, obsolescence, contradictions, unreliable sources, and duplication. The second aim is to explore different feedback mechanisms to indicate quality findings back to the communities. Third, the project will develop techniques to customize quality measurement and feedback to a particular developer's context. The resulting tools, data sets, and experimental infrastructure developed as part of the project will be released, enabling other researchers and practitioners to build on the project's results and ultimately advance the quality of the modern software development ecosystem.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.