coverage-analysis

To measure code coverage during fuzzing, compile your C/C++ or Rust targets with instrumentation like -fprofile-instr-generate -fcoverage-mapping, execute your corpus, and use llvm-profdata and llvm-cov to generate reports.

Fuzzing coverage analysis identifies which code paths are exercised by your corpus, enabling targeted harness improvements, blocker identification, and measurement of corpus effectiveness to guide dictionary and seed strategy.

Yes, you can use gcovr for coverage analysis on Rust and C/C++ fuzz targets that use GCC coverage instrumentation, producing reports to track progress and benchmark harness effectiveness across corpus updates.

To detect magic-value checks and blockers, analyze your coverage reports to identify unexecuted branches and hard-to-reach code paths, then use these insights to guide your dictionary and seed strategy.

The best way to compare harness effectiveness is to track coverage progress by generating reports with llvm-cov or gcovr after each corpus update and harness change, quantifying which code paths are newly exercised.

Yes, you need a runtime to execute the corpus against your instrumented builds, along with coverage tooling such as llvm-profdata, llvm-cov, or gcovr to process the collected data and produce coverage reports.