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coverage-analysis

Analyze code coverage from LLVM or GCC fuzzing campaigns to identify gaps.

9|4|Updated Feb 7, 2026
Search Tags:#instrumentation#coverage#llvm#fuzzing#harness#gcovr
One-click install
npx skills add https://github.com/marduk191/qwen3_mcp --skill coverage-analysis-marduk191
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: coverage-analysis
Source: https://github.com/marduk191/qwen3_mcp/tree/main/skills/testing-handbook-skills/skills/coverage-analysis
Command: npx skills add https://github.com/marduk191/qwen3_mcp --skill coverage-analysis-marduk191

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze code coverage during fuzzing campaigns to identify gaps and blockers.

Core Features & Use Cases

  • Instrument code with LLVM or GCC coverage to enable runtime data collection.
  • Generate and interpret reports using llvm-profdata/llvm-cov or gcovr.
  • Use coverage insights to guide harness improvements, dictionary entries, and test-case selection.

Quick Start

Run your fuzzing campaign with coverage instrumentation and generate a report to identify uncovered paths.

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 to find gaps during a fuzzing campaign?▼

Use this Skill to analyze code coverage during fuzzing campaigns by instrumenting code with LLVM or GCC coverage tools. It interprets reports from llvm-profdata, llvm-cov, or gcovr to identify uncovered paths and guide harness improvements.

Can I use gcovr to analyze code coverage for Rust fuzzing harnesses?▼

Yes, this Skill supports analyzing code coverage for Rust fuzzing harnesses using LLVM-based coverage tools or gcovr. It interprets runtime data to guide dictionary tuning and seed selection for Rust and C/C++ fuzzing workflows.

What is the best way to improve fuzzing harnesses using coverage data?▼

Improve fuzzing harnesses by instrumenting code with LLVM or GCC coverage, generating reports with llvm-profdata or gcovr, and using the coverage insights to tune dictionaries, select seeds, and modify harnesses to reach uncovered code paths.

Do I need LLVM instrumentation to analyze code coverage for fuzzing?▼

You need either LLVM or GCC-based instrumentation to enable runtime data collection for fuzzing coverage analysis. The Skill requires compatible tooling like llvm-profdata, llvm-cov, or gcovr to generate and interpret coverage reports.

Why does my fuzzing campaign have low code coverage despite running many iterations?▼

Low code coverage during a fuzzing campaign indicates gaps and blockers in your harness or inputs. Analyzing coverage reports from llvm-cov or gcovr identifies uncovered paths and guides harness improvements, dictionary tuning, and seed selection.

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