Abstract
Developers routinely integrate Stack Overflow code snippets into their codebases. However, the quality of snippets embedded in users’ answers remain elusive, and existing evaluations of code quality tend to be language or context-specific. Moreover, literature have found that contribution patterns vary depending on geographical locales, creating an unexplained rift between code quality, user location, and latent contextual regional factors.
The proposed study evaluates the quality of SQL, JavaScript, Python, Ruby, and Java snippets across reliability, readability, performance, and security dimensions, benchmarking findings across states in the USA and investigating how different diversity indicators correlate against code quality violations. The study culminates in a series of inductive content analyses that qualitatively supplement prior quality dimensions.
This replication package is provided for those interested in further examining our research methodology.