Software Development During COVID-19 Pandemic: an Analysis of Stack Overflow and GitHub
This work provides insights for researchers and practitioners in software engineering to understand and support pandemic-related projects, though it is incremental as it applies existing mining techniques to new data.
The study analyzed 1,190 questions from Stack Overflow and Data Science Q&A and 60,352 GitHub projects to identify trends in software development during the COVID-19 pandemic, finding correlations between questions and projects, with common topics including web scraping, data visualization, and machine learning using languages like Python and JavaScript.
The new coronavirus became a severe health issue for the world. This situation has motivated studies of different areas to combat this pandemic. In software engineering, we point out data visualization projects to follow the disease evolution, machine learning to estimate the pandemic behavior, and computer vision processing radiologic images. Most of these projects are stored in version control systems, and there are discussions about them in Question & Answer websites. In this work, we conducted a Mining Software Repository on a large number of questions and projects aiming to find trends that could help researchers and practitioners to fight against the coronavirus. We analyzed 1,190 questions from Stack Overflow and Data Science Q\&A and 60,352 GitHub projects. We identified a correlation between the questions and projects throughout the pandemic. The main questions about coronavirus are how-to, related to web scraping and data visualization, using Python, JavaScript, and R. The most recurrent GitHub projects are machine learning projects, using JavaScript, Python, and Java.