Understanding Emotions of Developer Community Towards Software Documentation
This research tackles the problem of insufficient and inconsistent software documentation for developers, aiming to improve project sustainability, but it is incremental as it applies existing sentiment analysis methods to new data.
The study analyzed sentiments in commit messages related to software documentation from 998 GitHub projects, finding that around 45% of the messages expressed trust emotion, to understand developer perceptions and address documentation issues.
The availability of open-source projects facilitates developers to contribute and collaborate on a wide range of projects. As a result, the developer community contributing to such open-source projects is also increasing. Many of the projects involve frequent updates and extensive reuses. A well-updated documentation helps in a better understanding of the software project and also facilitates efficient contribution and reuse. Though software documentation plays an important role in the development and maintenance of software, it also suffers from various issues that include insufficiency, inconsistency, ill-maintainability, and so on. Exploring the perception of developers towards documentation could help in understanding the reasons behind prevalent issues in software documentation. It could further aid in deciding on training that could be given to the developer community towards building more sustainable projects for society. Analyzing sentiments of contributors to a project could provide insights on understanding developer perceptions. Hence, as the first step towards this direction, we analyze sentiments of commit messages specific to the documentation of a software project. To this end, we considered the commit history of 998 GitHub projects from the GHTorrent dataset and identified 10,996 commits that correspond to the documentation of repositories. Further, we apply sentiment analysis techniques to obtain insights on the type of sentiment being expressed in commit messages of the selected commits. We observe that around 45% of the identified commit messages express trust emotion.