Test Coverage Analyzer
CautionAnalyze test coverage gaps, generate missing test cases, and improve test quality with mutation testing insights.
Install
Claude Code
claude install testing-coverage About This Skill
Overview
Test Coverage Analyzer goes beyond simple line coverage metrics to identify meaningful gaps in your test suite. It generates high-quality test cases that cover edge cases, error paths, and complex interactions that manual testing often misses.
Key Features
- Gap Analysis: Analyzes your codebase against existing tests to find untested functions, uncovered branches, and missing edge cases. Prioritizes gaps by risk — untested error handling and data validation get highest priority.
- Smart Test Generation: Generates tests that are meaningful, not just coverage-padding. Each test verifies specific behavior with clear assertions and descriptive names.
- Edge Case Detection: Identifies boundary conditions (empty arrays, null values, max integers, concurrent access) and generates specific tests for each.
- Mutation Testing Insights: Simulates code mutations to verify that tests actually catch bugs, not just execute code paths. Identifies tests that pass regardless of correctness.
Framework Support
Jest and Vitest for JavaScript/TypeScript, pytest for Python, cargo test for Rust, and JUnit for Java. Generates tests using framework-specific best practices and assertion libraries.
Test Patterns
Generates Arrange-Act-Assert structured tests with proper isolation. Includes fixture setup, mock configurations, and cleanup. Parameterized tests for data-driven scenarios.
Use Cases
- Identify untested code paths and generate targeted test cases
- Create edge case tests for boundary conditions and error paths
- Generate integration tests for API endpoints and database queries
- Analyze test quality beyond line coverage with branch and mutation testing
- Set up test infrastructure with proper fixtures and mocking patterns
Pros & Cons
Pros
- + Identifies high-risk untested code paths that matter most
- + Generated tests are readable and maintainable, not just coverage boosters
- + Mutation testing reveals weak tests that give false confidence
- + Supports all major testing frameworks with idiomatic patterns
Cons
- - Generated tests for complex business logic may need domain-specific assertions
- - Mutation testing analysis can be time-consuming on large codebases
- - Integration test generation requires running services or mock servers
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