Bullseye Code: Coverage

cov01 -1 # Instrument source make # Build covrun ./run_tests # Execute covhtml -o coverage_report *.cov # Generate HTML Automotive (ISO 26262 ASIL-D) In autonomous driving software, a single untested branch in a lane-keeping algorithm could cause a fatality. Bullseye is used to achieve Modified Condition/Decision Coverage (MC/DC) , which is required for ASIL-D. Bullseye’s reports can be directly submitted to certification auditors. Medical Devices (FDA Class III) The FDA requires objective evidence of test completeness. Bullseye’s ability to exclude TESTMARGIN regions (e.g., "this error handler is only for cosmic ray bit flips") and merge coverage from 10,000 hours of simulation is unmatched. Legacy Code Refactoring When taking over a million-line C++ codebase with 0% tests, Bullseye helps prioritize. Run a smoke test, generate a report, and refactor the red (uncovered) and yellow (partial) functions first. This risk-based testing approach saves months of effort. 6. Limitations and Critical Considerations No tool is perfect. Bullseye has notable constraints:

// After Bullseye instrumentation (conceptual) probe_1 = 0; // Counter for the decision if (temperature > 100 && pressure < 50) probe_1++; // Counts entry of the true branch activate_alarm(); bullseye code coverage

Introduction: The Evolution of Code Coverage Tools In the landscape of software quality assurance, code coverage metrics serve as the bedrock for understanding how thoroughly your tests exercise your application. While open-source tools like gcov (GCC) and lcov are widely known, the commercial sector has long relied on a powerful, precision-focused solution: Bullseye Coverage . cov01 -1 # Instrument source make # Build covrun

// Original code if (temperature > 100 && pressure < 50) activate_alarm(); Medical Devices (FDA Class III) The FDA requires