This strategy is a work in progress and everyone can contribute by sharing their feedback directly on GitLab.com, via e-mail, or Twitter.
While we strive to provide recommendations and checks around Code Quality in real time and through static analysis, we believe there are a lot more insights about our code that can be drawn from our repositories. Moreover, our codebase is usually a complex system, which has to be understood well in order to be managed well under time and money constraints. With more and more companies adopting agile practices and suffering from high attrition, understanding and modifying code can become a challenging task.
We would like to help Engineering Managers identify problematic patterns and prioritize changes to the codebase that would provide the most value. In order to do that, we will start with addressing the following questions:
We believe the target audience for Code Analytics is Engineering Management, who seeks to understand their codebase and to take data driven prioritization and management decisions.
In our first release containing Code Analytics MVC, we will provide a definition and visual representation of hotspots as well as language usage trends.
Visualize the number of lines of code and trends thereof for each language in our repositories.