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coverage-analysis

Measure code coverage during fuzzing campaigns with LLVM/GCC tooling.

Updated Aug 23, 2026
Search Tags:#testing#reporting#instrumentation#coverage#fuzzing#harness
One-click install
npx skills add https://github.com/DobricLilujun/LabAgentSkill --skill coverage-analysis-dobriclilujun
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: coverage-analysis
Source: https://github.com/DobricLilujun/LabAgentSkill/tree/main/skillsHub/skills_scaling/testing-handbook-skills/skills/coverage-analysis
Command: npx skills add https://github.com/DobricLilujun/LabAgentSkill --skill coverage-analysis-dobriclilujun

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coverage analysis measures which parts of code are executed during fuzzing. It helps identify fuzzing blockers like magic value checks and tracks harness improvements over time.

Core Features & Use Cases

  • Instrumentation setup with LLVM/Clang, GCC, and Rust fuzzers
  • Execution and generation of per-campaign coverage reports
  • Guidance for harness improvements, dictionary tuning, and regression monitoring
  • Use Case: Compare coverage between fuzzing campaigns to target uncovered code regions

Quick Start

Install LLVM-based coverage tooling, instrument your project, run your fuzzing campaign against a corpus, and generate the 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 code coverage during fuzzing?▼

Code coverage during fuzzing is measured by instrumenting your project with LLVM or GCC tooling, running the campaign against a corpus, and generating a report to reveal exercised code paths.

Can I use this coverage analysis with Rust fuzzers and C/C++ projects?▼

Yes, coverage analysis supports fuzzing campaigns across C/C++, Rust, and multi-language SUTs by utilizing standard LLVM-based and GCC coverage tooling for instrumented builds.

Why does my fuzzing campaign not reach deep code paths?▼

Fuzzing campaigns often miss deep code paths due to blockers like magic value checks, which coverage analysis helps identify by tracking harness improvements and dictionary tuning.

What is the best way to compare code coverage between fuzzing campaigns?▼

The best way to compare coverage between campaigns is to generate per-campaign coverage reports, allowing you to target uncovered code regions and monitor regressions over time.

Do I need a reproducible harness to generate fuzzing coverage reports?▼

Yes, generating fuzzing coverage reports requires a reproducible harness along with standard LLVM/GCC coverage tooling to execute instrumented builds and document the steps for report generation.

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