CodeScene lets you uncover and prioritize code that’s hard to maintain or parts of the code that become team productivity bottlenecks.
As such the techniques are reactive. Wouldn’t it be great if we could catch such problems much earlier, ideally before they are even delivered to our main branch?
In this blog post we explore a new feature of CodeScene that turns the analyses into a pro-active tool for early feedback. You’ll see how CodeScene offers the ability to detect maintenance problems and early warnings in your codebase by integrating the analysis results into your build pipeline and/or as robot comments in a code review tool like Gerrit.
Fight reviewer fatigue
The challenge with all preventive and corrective techniques is that they require time and discipline. Let’s take code reviews as an example. Code reviews done right are a proven defect removal technique. A code review is also an opportunity for knowledge sharing and learning. However, none of those benefits come for free.
Like all manual processes code reviews are hard to scale. As your organization grows, code reviewer fatigue becomes a real thing; There’s just so many lines of code you can review each day. Beyond that point you’re likely to slip. The result is increased lead times, bugs that pass undetected to production, and – in extreme cases – the risk for burnout.
At Empear we’ve developed a system for automated risk classifications to prioritize the code we need to review. The risk classification is built into CodeScene, which exposes a REST API that lets you integrate the classification into your continuous integration pipeline. The following figure shows an example from a Jenkins build: