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Coverage analysis measures code exercised during fuzzing.
Passed 22 of 22 test cases with the skill, and 18 of 22 without it.
and 2 more in the full report
4 fixed18 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
We are evaluating two successive seed batches using a GCC gcov build. After analyzing batch 1, we want to reset the accumulated GCC execution counters before running batch 2. What tool command clears these .gcda files?
| Checked | Without skill | With skill |
|---|---|---|
| uses gcovr --delete to clear existing gcda profile files | Missed | Passed |
The instructions your model reads when the skill loads.
Coverage analysis is essential for understanding which parts of your code are exercised during fuzzing. It helps identify fuzzing blockers like magic value checks and tracks the effectiveness of harness improvements over time.
Code coverage during fuzzing serves two critical purposes:
Coverage is a proxy for fuzzer capability and performance. While coverage is not ideal for measuring fuzzer performance in absolute terms, it reliably indicates whether your harness works effectively in a given setup.
| Concept | Description |
|---|---|
| Coverage instrumentation | Compiler flags that track which code paths are executed |
| Corpus coverage | Coverage achieved by running all test cases in a fuzzing corpus |
| Magic value checks | Hard-to-discover conditional checks that block fuzzer progress |
| Coverage-guided fuzzing | Fuzzing strategy that prioritizes inputs that discover new code paths |
| Coverage report | Visual or textual representation of executed vs. unexecuted code |
Apply this technique when:
Skip this technique when:
test cases passed, vs 18 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.