Bullseye Code Coverage ✦ Newest

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:

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? bullseye code coverage

This article provides a deep dive into the architecture, methodology, unique features, and strategic implementation of Bullseye Code Coverage. Bullseye is not just a line counter; it is a decision coverage tool. Its core philosophy is that simply knowing which lines of code executed (line coverage) is insufficient for identifying hidden logical flaws. cov01 -1 # Instrument source make # Build covrun

// The tool tracks both true and false evaluations. Medical Devices (FDA Class III) The FDA requires

Developed by Bullseye Testing Technology, Bullseye Coverage is a proprietary code coverage tool designed for C, C++, and C# environments. Unlike many modern, IDE-integrated plugins, Bullseye has carved a niche for itself in highly regulated industries (automotive, medical devices, aerospace) where functional safety and certification (ISO 26262, DO-178C, IEC 61508) are non-negotiable.

set(CMAKE_C_COMPILER "covc" CACHE STRING "") set(CMAKE_CXX_COMPILER "covc" CACHE STRING "") set(CMAKE_CXX_COMPILER_LAUNCHER "" CACHE STRING "") set(CMAKE_C_COMPILER_ARG1 "--compiler" CACHE STRING "") set(CMAKE_CXX_COMPILER_ARG1 "--compiler" CACHE STRING "") export PATH=/usr/local/bullseye/bin:$PATH covselect --add --on # Turn on coverage measurement cmake -DCMAKE_TOOLCHAIN_FILE=bullseye-toolchain.cmake .. covbuild cmake --build . --parallel Step 3: Run Tests & Capture Data cov01 -1 # Reset counters to zero ./bin/my_unit_tests covrun ./bin/integration_tests Step 4: Merge & Report covmerge -a *.cov # Merge all .cov files into one covhtml --title "Sprint 23 Coverage" -o coverage_html coverage.cov Step 5: Set a Quality Gate In your CI script, fail the build if decision coverage drops below 80%:

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: