CodeScene is a behavioral code analysis tool that serves as a data-driven project management software.
In this article we explore how CodeScene lets you measure where you spend your costs and how you can guide on- and off-boardings with data. This information is useful to bridge the gap between the technical side of the organization and the business side, as you let non-technical managers peek into the codebase and put actual numbers on the cost of any technical debt in the code.
The Need for Cost Metrics
CodeScene’s project management metrics answer two common questions:
- How shall we prioritize improvements to our codebase?
- How can we follow-up on the effects of the improvements we do? Did we really get an effect out of that design improvement?
CodeScene’s technical analyses addresses these questions by giving us a tool to prioritize technical debt. However, there’s a linguistic chasm between developers and managers here: to a manager, a technical concept like “code complexity” might not carry much meaning. At the same time, technical debt and low quality code are important subjects to address. So how can we communicate in the language of a manager while still tying our data back to something that carries meaning for the developers responsible for the code?
CodeScene bridges this chasm by introducing a suite of project management metrics. These metrics combine our existing behavioral code analyses with data from project management software like JIRA, where CodeScene extracts time-based costs (i.e. minutes of time to completion) or story point reports. CodeScene then analyze how those costs are distributed across the different parts of your codebase. This highlights your applications hotspots as measured by cost rather than technical metrics. Let’s look at an example.