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mutation-testing突变测试

Agent Skill

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

总安装

539

周安装

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GitHub Stars

1

下载量

174
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:mutation-testing(突变测试)
来源仓库:https://github.com/codyswanngt/lisa
仓库路径:skills/mutation-testing
安装命令:
npx skills add https://github.com/codyswanngt/lisa --skill mutation-testing
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/codyswanngt/lisa --skill mutation-testing

简介

mutation-testing 实施变异测试流程,生成目标代码变异体并筛选有效样本。

  • 适用于强化测试套件,通过消灭存活变异体提升测试覆盖率。
  • 默认处理当前分支变更文件,也可指定目录或单个源文件。
  • 安装前请确认测试框架是否支持变异插件,如 Stryker 或 PIT。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

AI-Powered Mutation Testing

Target: $ARGUMENTS

If no argument provided, default to files changed in the current branch (via git diff).

This skill implements the mutation testing workflow: generate targeted mutants, filter unproductive ones, run tests to find survivors, and harden the test suite by strengthening or creating tests that kill surviving mutants.

Step 1: Gather Context

1a. Identify Target Files

Determine what to mutate based on $ARGUMENTS:

  1. File path — Mutate the specified source file
  2. Directory — Mutate source files in the directory (exclude test files)
  3. No argument — Use git diff to find changed source files: git diff --name-only $(git merge-base HEAD main)...HEAD -- '*.ts' '*.tsx' ':!*.spec.*' ':!*.test.*'

If no target files found, notify the user and stop.

1b. Gather Supporting Context

For each target source file, collect:

  1. Source code — Read the full file contents
  2. Existing tests — Find corresponding test files (*.spec.ts, *.test.ts) via naming convention or import analysis
  3. Test coverage — Run tests with coverage for the target file to identify uncovered lines: bun run test -- --coverage --collectCoverageFrom='<target-file>' --silent 2>&1 | tail -20
  4. Recent git history — Check for recent defects or frequent changes: git log --oneline -10 -- <target-file>
  5. Risk factors — Assess which risk factors apply to each file:
Risk FactorIndicators
Data security / complianceHandles PII, auth, authorization, encryption, tokens
IntegrationsExternal API calls, HTTP clients, webhooks, message queues
Code vs data modelDatabase queries, ORM entities, schema validation
Historic defectsFrequent bug-fix commits, complex conditional logic
Change impactExported utility functions, shared modules, base classes
PerformanceLoops over large datasets, recursive calls, caching logic

1c. Determine Test Runner

Detect the project's test framework from package.json scripts and devDependencies:

  • Jest: bun run test
  • Vitest: bun run test
  • Other: adapt accordingly

Step 2: Generate Mutants

2a. Create Experimental Branch

git stash --include-untracked || true
git checkout -b mutation-testing/$(date +%Y-%m-%d-%H%M%S)
git stash pop || true

2b. Generate Risk-Factor-Guided Mutants

For each target source file, generate 3-5 mutants that target the identified risk factors. Apply these mutation operators:

Operator TypeExamples
Decision mutationsChange > to >=, && to `\\, === to !==`
Value mutationsChange constants, swap string literals, alter numeric values
Statement mutationsRemove guard clauses, delete error handling, skip validation
Integration mutationsRemove timeout handling, skip error code checks, bypass retry logic
Security mutationsRemove auth checks, bypass input validation, expose sensitive data in logs

For each mutant, produce:

  1. Mutant ID — Sequential identifier (M001, M002, etc.)
  2. File and line — Exact location of the change
  3. Mutation description — What was changed and why
  4. Risk factor — Which risk factor this targets
  5. The code change — A minimal, atomic edit to introduce the defect

Mutant quality criteria — Each mutant must be:

  • Non-trivial — Not just whitespace, comments, or formatting
  • Buildable — The project must still compile/typecheck
  • Realistic — Simulates a plausible programming error
  • Targeted — Addresses a specific risk factor
  • Atomic — Exactly one logical change per mutant

2c. Apply and Validate Each Mutant

For each generated mutant, one at a time:

  1. Apply the mutation — Edit the source file to introduce the defect
  2. Build check — Run bun run typecheck to verify the project still compiles

- If build fails: discard the mutant, revert the change, log failure reason, continue to next

  1. Commit the mutantgit commit -am "mutant: M00X - <description>"

Step 3: Filter Mutants

3a. Run Tests Against Each Mutant

Process mutants in reverse order (LIFO — latest commit first):

  1. Run relevant tests against the mutant: bun run test -- <test-file-path> --silent 2>&1
  2. Evaluate result:

- Test fails (mutant killed) → Revert the mutant commit. Log as killed. Proceed to next mutant. - Test passes (mutant survived) → The mutant reveals a test gap. Keep it for Step 4.

3b. Equivalence Detection for Surviving Mutants

For each surviving mutant, verify it is not semantically equivalent to the original:

  1. AST-level comparison — Compare the diff. If the change is purely syntactic (reordering independent statements, renaming to equivalent aliases), discard it.
  2. Behavioral analysis — Reason about whether any input could distinguish the mutant from the original:

- If no distinguishing input exists → Discard as equivalent - If a distinguishing input exists → Keep as a unique actionable mutant - If uncertain → Keep and flag for human review

3c. Record Mutant Metadata

For each mutant, maintain a record:

{
  "mutant_id": "M001",
  "file": "<source-file>",
  "line": 42,
  "risk_factor": "Data security / compliance",
  "description": "Removed authentication check before data access",
  "status": "survived|killed|equivalent|discarded",
  "commit_hash": "<hash>",
  "tests_run": ["test-file.spec.ts"],
  "equivalence_result": "not_equivalent|equivalent|uncertain"
}

Print a summary table after filtering:

| Mutant | File | Risk Factor | Status |
|--------|------|-------------|--------|
| M001   | ... | ...          | survived |
| M002   | ... | ...          | killed   |

Step 4: Harden Test Suite

For each surviving, non-equivalent mutant:

4a. Determine Test Strategy

  1. Existing test covers the mutated region → Strengthen the existing test
  2. No test covers the mutated region → Generate a new test

4b. Strengthen Existing Test or Generate New Test

When strengthening an existing test, modify the test to:

  • Add assertions that detect the behavioral difference introduced by the mutant
  • Add or modify test inputs that expose the defect in the mutant code
  • Preserve the test method name, signature, and overall structure
  • Avoid adding trivial or unrelated checks

When generating a new test, create a test that:

  • Specifically exercises the behavioral difference between original and mutant code
  • Uses strong, precise assertions that detect the exact defect
  • Focuses on the identified risk factor
  • Includes realistic test data that exposes the mutant's flawed behavior
  • Follows existing test naming conventions and structure from the codebase

4c. Validate Each Test (3-attempt limit)

For each improved or new test, validate with up to 3 attempts:

  1. Revert the mutant — Switch to original code
  2. Build check — Ensure the test compiles
  3. Run on original code — Test must PASS on unmodified code
  4. Re-apply the mutant — Switch back to mutated code
  5. Run on mutant code — Test must FAIL on the mutant

If validation fails, refine the test (up to 3 total attempts). If still failing after 3 attempts, flag for manual review.

4d. Apply Decision Matrix

Classify each test result:

Original CodeMutant CodeSignalAction
Builds + PassesBuilds + FailsStrong detectionKeep — alert developer
Builds + PassesBuilds + PassesWeak assertionRefine — strengthen assertion
Builds + FailsBuilds + PassesBad testDiscard — generate new test
Doesn't buildAnyBroken testDiscard — generate new test
Builds + PassesDoesn't buildUntestable mutantDiscard — notify developer
Builds + FailsBuilds + FailsAmbiguous signalDiscard — generate new test

4e. Finalize Tests

For each validated test:

  1. Add an inline comment above the test referencing the mutant: // Test hardened to kill mutant M001 (Risk Factor: Data security / compliance)
  2. Commit the test improvement to the experimental branch

Step 5: Cleanup and Report

5a. Revert All Mutants

Remove all mutant commits from the experimental branch, keeping only test improvements:

# Revert mutant commits (identified by "mutant:" prefix in commit message)
git log --oneline | grep "^.* mutant:" | awk '{print $1}' | while read hash; do
  git revert --no-commit "$hash"
done
git commit -m "chore: revert all mutants after test hardening"

5b. Validate Clean State

  1. Run full test suite on the clean code with test improvements: bun run test 2>&1
  2. All tests must pass. If any fail, investigate and fix.

5c. Report Results

Print a comprehensive mutation testing report:

## Mutation Testing Report

**Target**: <files tested>
**Date**: <timestamp>
**Branch**: <experimental branch name>

### Summary
- Total mutants generated: X
- Killed by existing tests: X
- Survived (test gaps found): X
- Equivalent (discarded): X
- Build failures (discarded): X
- **Mutation Score**: X% (killed / (total - equivalent))

### Test Improvements
- Tests strengthened: X
- New tests generated: X
- Tests validated successfully: X
- Tests requiring manual review: X

### Surviving Mutants (Unresolved)
| Mutant | File | Line | Risk Factor | Description |
|--------|------|------|-------------|-------------|
| M00X   | ...  | ...  | ...         | ...         |

### Oracle Gap
- Code coverage: X%
- Mutation score: X%
- Oracle gap: X% (coverage - mutation score)

### Risk Factor Coverage
| Risk Factor | Mutants | Killed | Survived | Score |
|---|---|---|---|---|
| Data security | X | X | X | X% |
| Integrations  | X | X | X | X% |

5d. Present Options

Ask the user:

  1. Merge test improvements — Cherry-pick test commits to the original branch, delete experimental branch
  2. Keep experimental branch — For further review before merging
  3. Discard everything — Delete the experimental branch, no changes kept

If the user chooses to merge:

git checkout <original-branch>
git cherry-pick <test-improvement-commits>
git branch -D <experimental-branch>

Never

  • Modify test files to make them pass on mutants (defeats the purpose)
  • Generate mutants in test files (only mutate source code)
  • Skip the build check after generating a mutant
  • Commit mutants to protected branches (dev, staging, main)
  • Leave mutant code in the codebase after completion
  • Generate more than 5 mutants per file (diminishing returns)
  • Skip equivalence detection for surviving mutants
  • Mark a test as valid without running it on both original and mutant code
  • Use --no-verify with any git command

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02

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.12%
按下载量换算59

Claude

30.46%
按下载量换算53

Cursor

18.4%
按下载量换算32

Gemini CLI

9.65%
按下载量换算17

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可疑

Snyk

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