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Category Strategy - Code Analytics

Manage Stage

Stage Maturity
Manage Minimal

Introduction and how you can help

Thank you for visiting the category strategy page for Code Analytics. This page belongs to Virjinia Alexieva (E-Mail, Twitter).

This strategy is a work in progress and everyone can contribute by sharing their feedback directly on GitLab.com, via e-mail, or Twitter.

Overview

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.

Where we are Headed

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:

Target Audience and Experience

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.

What's Next & Why

In our first release containing Code Analytics MVC, we will provide a definition and visual representation of hotspots as well as language usage trends.

Maturity Plan

This category is currently at the Minimal maturity level and our next maturity target is Viable by October 2019. Please see our definitions of maturity levels and related epics.

Competitive Landscape

Code Scene

Sonar Source

Codacy

Code Climate

Top user issue(s)

Visualize the number of lines of code and trends thereof for each language in our repositories.