I'm curious about how organizations effectively measure code quality, especially when managing large teams, like 10,000 engineers. We often hear that high code coverage doesn't necessarily mean high code quality. With various organizational and industry standards in place, what metrics do you all utilize to ensure that the quality remains high? Given that reviewing every PR manually isn't feasible, and constant monitoring of the entire codebase is unrealistic, do you rely on tools like SonarQube to identify code smells? Additionally, when standards evolve, should we do an entire rescan of the codebase? Beyond just stability metrics like bug counts—which feels reactive—what proactive measures or systems do you have in place to highlight areas needing attention? Ideally, I envision a tool that aligns with our standards and provides a heat map highlighting critical parts of the codebase that require focus.
5 Answers
I totally see where you're coming from. Larger teams usually have leads who can enforce standards, but it's about more than just enforcement. The metrics that matter are things like flakiness of tests, deployment times, and how often changes are reverted. It all boils down to having reliable tests that can catch potential bugs. With those in place, you create a culture where engineers care about the quality of their code more effectively.
At past jobs, I saw metrics being misused. Sure, tracking test coverage can help, but after a point, if it’s not genuinely reflective of quality, you end up with teams just gaming the numbers. I believe a culture focused on understanding the automation process is crucial. Tracking metrics like how often your tests fail when they shouldn't is far more telling. Over time, this approach allows you to pinpoint which parts of your codebase need more attention or a refactor because of chronic problems.
Absolutely! We've all experienced those codes that just sit there and fall behind. How do you uncover those inefficiencies?
While it sounds simple, good code is often subjective. As long as the code is functional, it’s typically deemed good enough. Utilizing formatters or linters can help maintain standards across the board, and solid tests ensure functionality. On top of that, if you haven’t already, introducing performance tests could really enhance your critical processes!
I get that! But how do you evaluate test quality if you can't solely depend on code reviews?
That's a tough one! Honestly, I think many organizations struggle with this. You know, code coverage might give a bit of insight, but it can be subjective. Tools like CI tech can catch basic errors, but they often miss fundamental issues. Finding the right balance is key. Also, it can be more productive to foster a culture around quality rather than chasing a perfect score on coverage metrics. You might want to look into how often your test suites are failing or how quickly you can deploy. These factors can tell you a lot about your code quality.
How do you stay on top of areas that are losing quality over time? I mean, there's always some legacy code that starts to rot, right?
Ultimately, I believe that code is merely a reflection of requirements. To measure the quality efficiently, I use black-box testing, which focuses strictly on whether the requirements are being met, with no need for inspecting the code itself. It's about ensuring the outputs are right based on given inputs. Test coverage seems secondary; what matters more is that the tests can discern when code is redundant or unnecessary.
So to clarify, you suggest monitoring outcomes instead of code state? That makes sense!
Great points! But how do you monitor code that isn't regularly updated? What if a tool from a year ago is just stagnant?