When it comes to safety-critical systems—like aviation software or automotive control units—accuracy in testing is non-negotiable. That’s where MC/DC coverage (Modified Condition/Decision Coverage) comes into play. It ensures that every condition in a decision has been shown to independently affect the outcome, providing a rigorous level of testing beyond simple code or branch coverage.

By focusing on logical relationships within the code, MC/DC coverage helps identify hidden dependencies that might otherwise go unnoticed. This makes it a preferred standard in compliance frameworks like DO-178C and ISO 26262.

While implementing MC/DC coverage can be challenging, tools that automate condition tracking and test case generation make it more achievable. Investing in this metric isn’t just about meeting standards—it’s about building systems you can trust.

In software testing, code coverage has long been seen as a key indicator of test completeness — but relying on it alone can create a false sense of confidence. High coverage percentages may look impressive, yet they don’t always mean that the most critical or high-risk parts of an application are thoroughly tested.

For instance, a test might execute a line of code without actually validating its logic or outcome. This is where teams are now shifting focus from how much code is covered to how well it’s being tested. Techniques like mutation testing, branch coverage, and path analysis are helping QA engineers uncover untested behaviors and logical gaps that simple coverage metrics might overlook.

The goal is to use code coverage as one piece of a larger quality picture — combined with metrics like defect density, test effectiveness, and performance indicators. Modern CI/CD pipelines now integrate these insights to provide more actionable feedback to developers.