One of the biggest challenges in software testing today is not the lack of data, but how to interpret it. Test reports, coverage percentages, execution statistics… all are important, but when seen only in spreadsheets, it becomes difficult to quickly identify where the issues lie.
This is exactly where visual data analysis helps: a well-designed visualization can immediately show where test coverage is weak, which code segments are untested, and where more attention is needed.
Why are numbers not enough?
Most test coverage reports display percentage values. But these numbers don’t reveal which code parts were missed during testing or the risks they carry. High overall coverage is meaningless if the remaining 20% includes the most critical functions. That’s why it’s important not to just measure but also to see what’s being tested. TestNavigator displays the code areas covered during test executions in a visual, comprehensible manner, allowing easy monitoring of the actual testing state.
Benefits of Visual Test Analysis
Visual test coverage reports help both developers and testers interpret results more easily. Some examples of such visualizations include:
- HeatMap – uses colors to show which packages, classes, or methods have been least tested.
- Code-level view – shows, line by line, which parts were hit by tests and which were not.
- Trend charts – display how coverage has changed between versions.
- Complexity metrics – help identify modules that require more thorough testing.
These visual tools not only save time but also highlight critical points, significantly increasing the efficiency of the testing process.
Where Transparency Meets Efficiency
TestNavigator is a solution built specifically for visualization and test coverage data analysis. With the platform, teams can:
- monitor real coverage values in real time,
- visually identify untested code segments,
- easily prioritize test cases to ensure important scenarios are not missed,
- and view the complete state of testing from a single interface.
The HeatMap view, for example, instantly shows which modules were untouched during testing and which parts need additional tests. This facilitates more effective collaboration between developers and testers, as everyone shares a single real-time picture. No more misunderstandings or lost Excel sheets.
How Visualization Boosts Testing Efficiency
Visualization greatly improves testing efficiency by exposing weak areas at a glance. The testing team can therefore work more targetedly and focus on truly critical code segments. Moreover, visually presented data is easily understandable for all stakeholders, not just testers, which improves communication. Management also gains a clearer picture of quality status, leading to more informed decision-making. All of this helps ensure fewer bugs reach production, as issues are caught earlier in development.
Testing Efficiency = Business Value
Efficient testing brings not only technical advantages but also business security. With visual coverage data, teams can accurately assess the risk of releasing a version and determine when a project reaches "Go" status. This gives companies a significant edge over their competitors.