A Software Requirements Ecosystem: Linking Forum, Issue Tracker, and FAQs for Requirements Management

User feedback is an important resource in modern software development, often containing requirements that help address user concerns and desires for a software product. The feedback in online channels is a recent focus for software engineering researchers, with multiple studies proposing automatic analysis tools. In this work, we investigate the product forums of two large open source software projects. Through a quantitative analysis, we show that forum feedback is often manually linked to related issue tracker entries and product documentation. By linking feedback to their existing documentation, development teams enhance their understanding of known issues, and direct their users to known solutions. We discuss how the links between forum, issue tracker, and product documentation form a requirements ecosystem that has not been identified in the previous literature. We apply state-of-the-art deep-learning to automatically match forum posts with related issue tracker entries. Our approach identifies requirement matches with a mean average precision of 58.9% and hit ratio of 82.2%. Additionally, we apply deep-learning using an innovative clustering technique, achieving promising performance when matching forum posts to related product documentation. We discuss the possible applications of these automated techniques to support the flow of requirements between forum, issue tracker, and product documentation.

Automated summary

User feedback is a valuable resource in software development, and analyzing feedback from online channels has gained attention from researchers. In this study, we analyze the feedback in the product forums of two open source software projects and find that it is often linked to issue tracker entries and product documentation. By linking feedback to existing documentation, development teams gain a better understanding of known issues and provide users with known solutions. We apply deep-learning techniques to match forum posts with issue tracker entries and product documentation, achieving promising results.