Empirical Study of the Evolution of Python Questions on StackOverflow

Syam, Gopika; Lal, Sangeeta; Chen, Tao; Sangeeta, Sangeeta

Abstract

Background: Python is a popular and easy-to-use programming language. It is constantly expanding, with new features and libraries being introduced daily for a broad range of applications. This dynamic expansion needs a robust support structure for developers to effectively utilise the language.

Aim: In this study we conduct an in-depth analysis focusing on several research topics to understand the theme of Python questions and identify the challenges that developers encounter, using the questions posted on Stack Overflow.

Method:We perform a quantitative and qualitative analysis of Python questions in Stack Overflow. Topic Modelling is also used to determine the most popular and difficult topics among developers.

Results: The findings of this study revealed a recent surge in questions about scientific computing libraries pandas and TensorFlow. Also, we observed that the discussion of Data Structures and Formats is more popular in the Python community, whereas areas such as Installation, Deployment, and IDE are still challenging.

Conclusion: This study can direct the research and development community to put more emphasis on tackling the actual issues that Python programmers are facing.

Citation

Syam, G., Lal, S., Chen, T., & Sangeeta, S. (2023). Empirical Study of the Evolution of Python Questions on StackOverflow. e-Informatica Software Engineering Journal (EISEJ), 17(1), 230107. https://doi.org/10.37190/e-inf230107

• Journal Article Type: Article
• Acceptance Date: Jun 30, 2023
• Publication Date: 2023
• Deposit Date: Mar 8, 2024
• Journal: e-Informatica Software Engineering Journal (EISEJ)
• Print ISSN: 1897-7979
• Publisher: Software Engineering Section of the Committee on Informatics of the Polish Academy of Sciences
• Peer Reviewed: Peer Reviewed
• Volume: 17
• Issue: 1
• Pages: 230107
• DOI: https://doi.org/10.37190/e-inf230107
• Keywords: Python programming, Software Development, Stack Overflow, Topic Modelling
• Public URL: https://keele-repository.worktribe.com/output/762753