Context
A well-tested project with no metrics to prove it
Following an external code quality audit on a large industrial C++ project, our client identified a critical issue: the complete absence of code coverage metrics. The audit recommended a minimum of 80% test coverage for a project of this size. However, the team had no way of knowing how much of their existing tests were actually covering the code.
To address this visibility gap and accurately assess the impact of current tests, the client asked us to implement an integrated code coverage analysis system within their GitLab ecosystem.
Our approach
CI-based test execution and automated coverage reports
We automated the execution of unit tests using a DevOps approach, embedding them into the project’s continuous integration (CI) pipeline. Alongside unit testing, we implemented static code analysis and an integration testing infrastructure.
A code coverage analysis system was deployed to provide high-level statistics and detailed reports identifying which parts of the code were covered and which weren’t. The entire solution was fully integrated with GitLab, enabling a smooth and continuous testing workflow.
Results
Enhanced visibility and a smoother developer experience
Automating the tests and integrating them into CI significantly improved the development workflow. Regressions can now be detected before being merged into the main project. Code coverage tracking ensures that new code is properly tested and helps the team strategically expand their tests to meet the 80% goal.
With these metrics in place, the client gains a clear view of test efficiency and can identify gaps in coverage with precision. The result: stronger code quality, better-informed decisions and a development team with the tools to move faster and smarter.
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