Mutation Testing Improvement Planner

The problem

High code coverage often hides weak assertions and missing behavioral tests that fail to detect real defects. Developers struggle to prioritize surviving mutants from tools like Stryker or PIT, often wasting time on equivalent mutants or chasing scores instead of addressing business risk.

What it does

• Analyzes mutation testing reports to distinguish between genuine test weaknesses and equivalent or low-value mutants.
• Identifies over-mocked boundaries where tests execute code but fail to validate actual outcomes.
• Maps surviving mutants to business-critical behaviors to prioritize fixes that impact data integrity or security.
• Recommends the specific test layer (unit, integration, or contract) best suited to kill surviving mutants.
• Provides a 100-point test-strength score and a prioritized plan for test additions and configuration adjustments.

Frameworks & tools

Compatible with Stryker, PIT (PITest), mutmut, and Infection. Works across languages including Java, JavaScript, TypeScript, PHP, and Python.

Why this beats prompting it yourself

Standard LLM prompts often treat every surviving mutant as a bug to be fixed. This skill uses a specialized rubric to identify semantic equivalency and risk-weighted priorities, preventing you from bloating your test suite with redundant or brittle assertions.

Use cases

• Reviewing pull requests to ensure new code meets mutation-testing thresholds.
• Auditing legacy test suites to find "execution-only" tests that lack meaningful assertions.
• Classifying equivalent mutants to clean up noisy reports and focus on real gaps.
• Designing targeted integration tests for mutants that unit tests cannot realistically reach.

Known limitations

Does not execute mutation tools or modify source code directly. Requires a pre-generated mutation report or list of surviving mutants to perform analysis.