I’ve been diving deeper into the role of code coverage in software testing and wanted to open a discussion here. While code coverage gives us a measurable way to see how much of the code is being exercised by our tests, I’ve noticed that having a high percentage doesn’t always mean the tests are effective or that critical bugs are being caught.
From what I understand, there are multiple approaches — like statement coverage, branch coverage, and condition coverage — each giving different insights into how well the application logic is validated. The challenge, though, is figuring out how to balance the effort of writing tests for higher coverage with the need for meaningful test scenarios.
Some teams I’ve read about integrate code coverage reports into their CI/CD pipelines, using them not as a strict KPI but more as a guiding metric to highlight areas that may need additional test focus. Tools like Keploy also play a role in capturing realistic test data to improve coverage without adding unnecessary overhead.
So I’m curious to know: How do you and your teams approach code coverage in practice? Do you aim for a specific percentage target, or do you treat it more as a directional indicator? And what best practices have you found useful for making code coverage a meaningful part of your overall testing strategy?
Answered 4 months ago
Sophie Lane
I’ve been diving deeper into the role of code coverage in software testing and wanted to open a discussion here. While code coverage gives us a measurable way to see how much of the code is being exercised by our tests, I’ve noticed that having a high percentage doesn’t always mean the tests are effective or that critical bugs are being caught.
From what I understand, there are multiple approaches — like statement coverage, branch coverage, and condition coverage — each giving different insights into how well the application logic is validated. The challenge, though, is figuring out how to balance the effort of writing tests for higher coverage with the need for meaningful test scenarios.
Some teams I’ve read about integrate code coverage reports into their CI/CD pipelines, using them not as a strict KPI but more as a guiding metric to highlight areas that may need additional test focus. Tools like Keploy also play a role in capturing realistic test data to improve coverage without adding unnecessary overhead.
So I’m curious to know: How do you and your teams approach code coverage in practice? Do you aim for a specific percentage target, or do you treat it more as a directional indicator? And what best practices have you found useful for making code coverage a meaningful part of your overall testing strategy?