Understanding the Effect of Developer Sentiment on Fix-Inducing Changes: An Exploratory Study on GitHub Pull Requests

Abstract

Developer emotion or sentiment in a software development environment has the potential to affect performance, and consequently, the software itself. Sentiment analysis, conducted to analyze online collaborative artifacts, can derive effects of developer sentiment. This study aims to understand how developer sentiment is related to bugs, by analyzing the difference of sentiment between regular and Fix-Inducing Changes (FIC) - changes to code that introduce bugs in the system. To do so, sentiment is extracted from Pull Requests of 6 well known GitHub repositories, which contain both code and contributor discussion. Sentiment is calculated using a tool specializing in the software engineering domain: SentiStrength-SE. Next, FICs are detected from Commits by filtering the ones that fix bugs and tracking the origin of the code these remove. Commits are categorized based on FICs and assigned separate sentiment scores (-4 to +4) based on different preceding artifacts - Commits, Comments and Reviews from Pull Requests. The statistical result shows that FICs, compared to regular Commits, contain more positive Comments and Reviews. Commits that precede an FIC have more negative messages. Similarly, all the Pull Request artifacts combined are more negative for FICs than regular Commits.