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coverage-analysis

Measure coverage across fuzzing campaigns to identify untested code paths.

Updated Apr 5, 2026
Search Tags:#reporting#instrumentation#coverage#fuzzing#harness#llvm-cov#gcovr
One-click install
npx skills add https://github.com/balic-AI-ML-R-D-Resources/eliza_autonomous_agents --skill coverage-analysis-balic-ai-ml-r-d-resources
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: coverage-analysis
Source: https://github.com/balic-AI-ML-R-D-Resources/eliza_autonomous_agents/tree/main/packages/skills/skills/testing-handbook-skills/skills/coverage-analysis
Command: npx skills add https://github.com/balic-AI-ML-R-D-Resources/eliza_autonomous_agents --skill coverage-analysis-balic-ai-ml-r-d-resources

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coverage analysis helps identify fuzzing blockers, track harness effectiveness, and reveal untested code paths by collecting and interpreting coverage data across campaigns.

Core Features & Use Cases

  • Identify uncovered code blocks and magic value checks across campaigns.
  • Track coverage trends over time to measure improvements or regressions.
  • Integrates with LLVM-based tools (llvm-cov, gcovr) and cargo-fuzz coverage to generate reports.

Quick Start

Instrument your target with coverage flags, run your fuzzing campaign against a corpus, and generate a coverage report.

Frequently Asked Questions about coverage-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I measure fuzzing coverage to find untested code paths in C/C++?▼

To measure fuzzing coverage, instrument your C/C++ target with coverage flags, run a campaign against a corpus, and use llvm-cov or gcovr to generate per-file reports identifying uncovered code blocks.

What is the best way to track coverage trends over multiple fuzzing campaigns?▼

Track coverage trends by collecting and interpreting coverage data across campaigns. This reveals harness effectiveness and highlights regressions or improvements in untested code paths over time.

Can I use cargo-fuzz coverage to measure Rust fuzzing effectiveness?▼

Yes, cargo-fuzz coverage is supported for Rust projects. It integrates with LLVM-based tooling to generate runnable reports that reveal untested code paths and blocked paths in your fuzzing campaign.

Does coverage analysis require special instrumentation flags before fuzzing?▼

Yes, coverage analysis requires instrumenting the target with proper coverage flags before running your fuzzing campaign. This enables llvm-cov and gcovr to collect data and produce accurate per-file reports.

Why does fuzzing coverage reveal magic value checks and blocked paths?▼

Fuzzing coverage reveals blocked paths by identifying uncovered code blocks and magic value checks across campaigns. This highlights conditional logic that prevents the fuzzer from reaching deeper code paths.

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