Code Smells in React Projects of a Junior Enterprise
Resumo
This study investigates the prevalence and correlation of code smells in web projects developed by a Junior Enterprise (JE) using the React or Next.js framework. Through a quantitative analysis of 40 projects using the ReactSniffer2 tool and custom scripts, 14 distinct code smells were evaluated. The results reveal a high density of smells, averaging 19.4 occurrences per 1,000 lines of code (LOC). String Literals was identified as the most prevalent smell, occurring 4.75 times more frequently than Mutable Variables. Furthermore, the study identified eight strong correlations between smells, all of which reached statistical significance (𝑝 < 0.05). These findings provide empirical evidence to support the enhancement of developer training and curricula in student-led organizations, aiming to improve software maintainability and code quality early in these students’ careers.
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