Data Analysis project to explore the relationship between good software engineering practices and the quality of the produced code.
We developed a set of tools to analyze coding practices in the Technical Debt Dataset, with data providing from SonarQube reports on multiple open-source projects of different scale.
We used multiple variables from the data such as the number of commits, the severity of bugs created or the grammatical correctness of commit messages.
It was developed strictly following the CRISP-DM methodology.
The complete project report can be found here.