Exploring Popular Software Repositories: A Study on Sentiment Analysis and Commit Clustering

• Autor(a) principal: Vieira, Bianca Puerta Rocha [UNESP]
• Data de Publicação: 2024
• Outros Autores: Garcia, Rogério Eduardo [UNESP]
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.5220/0012633400003690; https://hdl.handle.net/11449/299442
• topic: Knowledge Discovery; Mining Software Repositories; Sentiment Analyses

The software repositories store data and metadata about the project development, including commits, which record user modifications to projects and their metadata, such as the user responsible for the commit, date, time, and others. The programmer can register a comment to inform the modification content, its purpose, requester, motivation, and useful data. Focusing on those comments, this paper proposes using comments to group the commits and construct a sentiment analysis regarding the messages. The main purpose is to analyze those messages, both by the groups and the sentiments expressed, to understand them (what sort of sentiment they express). Opinions are central to almost all human activities and are key influences on our behaviors. Beliefs, perceptions of reality, and choices made are conditioned upon sentiments. Therefore, understanding how the developers, especially programmers, feel about a task might be useful in analyzing progress and interaction among people and artifacts (source code). In this paper, we present initial analyses of data and metadata from the twenty most popular software repositories, written in five popular programming languages. We stated five research questions and answered them, pointing out further investigations.