Uncovering User Concerns and Preferences in Static Analysis Tools: a Topic Modeling Approach

Uncovering User Concerns and Preferences in Static Analysis Tools: a Topic Modeling Approach

연구 분야: Verification

학회: 2024 2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings)

In the field of software development, Static Analysis Tool (SAT) play a crucial role in maintaining code quality and identifying potential defects early in the development process. Despite their widespread use, there is limited research on understanding user feedback and sentiments towards these tools. This study aims to bridge this gap by applying topic modeling techniques to user reviews of four (4) popular Static Analysis Tools (SATs): SonarQube, PMD, Checkstyle, and FindBugs. Using a comprehensive dataset of user reviews collected from various online platforms, we identify prevalent themes and topics discussed by users. Our analysis highlights the key aspects that users find beneficial and areas where improvements are needed. The findings provide valuable insights into user concerns and preferences, informing the development of more user-friendly and effective SATs. Additionally, this study contributes to the growing body of knowledge on applying natural language processing (NLP) techniques to software engineering research, offering a framework for future studies on user feedback analysis.