Bullseye Code Coverage -

Use Bullseye if you need certifiable decision coverage in C/C++ embedded systems, or if you must merge coverage from thousands of test runs. Use open-source tools for web or mobile apps. Conclusion: Hitting the Bullseye Bullseye Coverage is not a glamorous tool. It has a dated UI, a command-line interface that feels like 1995, and a price tag. However, for safety-critical and mission-critical software, it remains the gold standard for decision coverage.

// The tool tracks both true and false evaluations. bullseye code coverage

of 100% would be achieved if a single test calls validate_user(25, true, false) . All lines execute. But have you tested all logical possibilities? Use Bullseye if you need certifiable decision coverage

The instrumented source is then compiled and linked with Bullseye’s runtime library. You run your test suite normally (unit tests, integration tests, fuzzing). As the binary executes, the probes increment counters in shared memory or a .cov data file. Bullseye is remarkably low-overhead—typically 10-30% slowdown, making it viable for large test suites. Phase 3: Merging & Reporting ( covselect , covbr , covhtml ) This is where Bullseye shines. You can run tests across 1000 different processes, on different machines, at different times, and then merge all the .cov files into a single aggregate report. The command covmerge intelligently sums counters without double-counting. 3. Deep Dive: Decision Coverage (The "True" Bullseye Metric) Many teams erroneously believe 100% line coverage equals "tested." Consider this C++ function: It has a dated UI, a command-line interface