Test Updates and Maintenance

测试更新与维护

Overview

概述

detailed test management system that applies TDD/BDD principles to maintain, generate, and enhance tests across codebases. This skill practices what it preaches - it uses TDD principles for its own development and serves as a living example of best practices.

这是一个遵循TDD/BDD原则的精细化测试管理系统，用于在代码库中维护、生成和优化测试。该技能以身作则——它自身的开发就采用了TDD原则，是最佳实践的鲜活示例。

Core Philosophy

核心理念

RED-GREEN-REFACTOR: Strict adherence to TDD cycle
Behavior-First: BDD patterns that describe what code should do
Meta Dogfooding: The skill's own tests demonstrate the principles it teaches
Quality Gates: detailed validation before considering tests complete

RED-GREEN-REFACTOR（红-绿-重构）：严格遵循TDD周期
行为优先：采用BDD模式描述代码应实现的功能
自我验证：该技能自身的测试展示了它所传授的原则
质量关卡：在认定测试完成前进行精细化验证

What It Is

功能介绍

A modular test management system that:

Discovers what needs testing or updating
Generates tests following TDD principles
Enhances existing tests with BDD patterns
Validate test quality through multiple lenses

这是一个模块化的测试管理系统，具备以下能力：

发现需要测试或更新的内容
遵循TDD原则生成测试
用BDD模式优化现有测试
从多个维度验证测试质量

Quick Start

快速开始

Quick Checklist for First Time Use

首次使用快速检查清单

validate pytest is installed (
```
pip install pytest
```
)
Have your source code in
```
src/
```
or similar directory
Create a
```
tests/
```
directory if it doesn't exist
Run
```
Skill(sanctum:git-workspace-review)
```
first to understand changes

Start with

Skill(test-updates) --target <specific-module>

for focused updates

确认已安装pytest（执行
```
pip install pytest
```
）
源代码放在
```
src/
```
或类似目录下
若不存在
```
tests/
```
目录则创建它
先运行
```
Skill(sanctum:git-workspace-review)
```
了解代码变更

执行

Skill(test-updates) --target <特定模块>

开始定向更新

detailed Test Update

全面测试更新

bash

undefined

bash

undefined

Run full test update workflow

运行完整的测试更新工作流

Skill(test-updates)

**Verification:** Run `pytest -v` to verify tests pass.

Skill(test-updates)

**验证方式：** 执行`pytest -v`确认测试通过。

Targeted Test Updates

定向测试更新

bash

undefined

bash

undefined

Update tests for specific paths

更新特定路径下的测试

Skill(test-updates) --target src/sanctum/agents Skill(test-updates) --target tests/test_commit_messages.py

**Verification:** Run `pytest -v` to verify tests pass.

Skill(test-updates) --target src/sanctum/agents Skill(test-updates) --target tests/test_commit_messages.py

**验证方式：** 执行`pytest -v`确认测试通过。

TDD for New Features

新功能的TDD实践

bash

undefined

bash

undefined

Apply TDD to new code

对新代码应用TDD

Skill(test-updates) --tdd-only --target new_feature.py

**Verification:** Run `pytest -v` to verify tests pass.

Skill(test-updates) --tdd-only --target new_feature.py

**验证方式：** 执行`pytest -v`确认测试通过。

Using the Scripts Directly

直接使用脚本

Human-Readable Output:

bash

undefined

人类可读输出：

bash

undefined

Analyze test coverage gaps

分析测试覆盖缺口

python plugins/sanctum/skills/test-updates/scripts/test_analyzer.py --scan src/

Generate test scaffolding

生成测试脚手架

python plugins/sanctum/skills/test-updates/scripts/test_generator.py
--source src/my_module.py --style pytest_bdd

Check test quality

检查测试质量

python plugins/sanctum/skills/test-updates/scripts/quality_checker.py
--validate tests/test_my_module.py

**Verification:** Run `pytest -v` to verify tests pass.

**Programmatic Output (for Claude Code):**
```bash

python plugins/sanctum/skills/test-updates/scripts/quality_checker.py
--validate tests/test_my_module.py

**验证方式：** 执行`pytest -v`确认测试通过。

**供Claude Code使用的程序化输出：**
```bash

Get JSON output for programmatic parsing - test_analyzer

获取用于程序化解析的JSON输出 - test_analyzer

python plugins/sanctum/skills/test-updates/scripts/test_analyzer.py
--scan src/ --output-json

Returns:

返回结果：

{

"success": true,

"data": {

"source_files": ["src/module.py", ...],

"test_files": ["tests/test_module.py", ...],

"uncovered_files": ["module_without_tests", ...],

"coverage_gaps": [{"file": "...", "reason": "..."}]

}

Get JSON output - test_generator

获取JSON输出 - test_generator

python plugins/sanctum/skills/test-updates/scripts/test_generator.py
--source src/my_module.py --output-json

Returns:

返回结果：

{

"success": true,

"data": {

"test_file": "path/to/test_my_module.py",

"source_file": "src/my_module.py",

"style": "pytest_bdd",

"fixtures_included": true,

"edge_cases_included": true,

"error_cases_included": true

}

Get JSON output - quality_checker

获取JSON输出 - quality_checker

python plugins/sanctum/skills/test-updates/scripts/quality_checker.py
--validate tests/test_my_module.py --output-json

Returns:

返回结果：

{

"success": true,

"data": {

"static_analysis": {...},

"dynamic_validation": {...},

"metrics": {...},

"quality_score": 85,

"quality_level": "QualityLevel.GOOD",

"recommendations": [...]

}

**Verification:** Run `pytest -v` to verify tests pass.

**验证方式：** 执行`pytest -v`确认测试通过。

When To Use It

适用场景

Use this skill when you need to:

Update tests after code changes
Generate tests for new features
Improve existing test quality
validate detailed test coverage

Perfect for:

Pre-commit test validation
CI/CD pipeline integration
Refactoring with test safety
Onboarding new developers

在以下场景中使用该技能：

代码变更后更新测试
为新功能生成测试
提升现有测试质量
验证测试的全面覆盖

尤其适合：

提交前的测试验证
CI/CD流水线集成
借助测试安全地重构代码
新开发者入职培训

When NOT To Use

不适用场景

Auditing test suites - use pensive:test-review
Writing production code
- focus on implementation first
Auditing test suites - use pensive:test-review
Writing production code
- focus on implementation first

审计测试套件——请使用pensive:test-review
编写生产代码——请先专注于实现
审计测试套件——请使用pensive:test-review
编写生产代码——请先专注于实现

Workflow Integration

工作流集成

Phase 1: Discovery

阶段1：发现

Scan codebase for test gaps
Analyze recent changes
Identify broken or outdated tests

See

modules/test-discovery.md

for detection patterns.

扫描代码库寻找测试缺口
分析近期代码变更
识别失效或过时的测试

详见

modules/test-discovery.md

中的检测模式。

Phase 2: Strategy

阶段2：策略

Choose appropriate BDD style (see
```
modules/bdd-patterns.md
```
)
Plan test structure
Define quality criteria

选择合适的BDD风格（详见
```
modules/bdd-patterns.md
```
）
规划测试结构
定义质量标准

Phase 3: Implementation

阶段3：实现

Write failing tests (RED) - see
```
modules/tdd-workflow.md
```
Implement minimal passing code (GREEN)
Refactor for clarity (REFACTOR)

See

modules/test-generation.md

for generation templates.

编写失败的测试（红阶段）——详见
```
modules/tdd-workflow.md
```
实现最小化的可通过代码（绿阶段）
重构代码以提升可读性（重构阶段）

详见

modules/test-generation.md

中的生成模板。

Phase 4: Validation

阶段4：验证

Static analysis and linting
Dynamic test execution
Coverage and quality metrics

See

modules/quality-validation.md

for validation criteria.

静态分析与代码检查
动态测试执行
覆盖度与质量指标

详见

modules/quality-validation.md

中的验证标准。

Quality Assurance

质量保障

The skill applies multiple quality checks:

Static: Linting, type checking, pattern validation
Dynamic: Test execution in sandboxed environments
Metrics: Coverage, mutation score, complexity analysis
Review: Structured checklists for peer validation

该技能会应用多维度的质量检查：

静态检查：代码检查、类型检查、模式验证
动态检查：在沙箱环境中执行测试
指标分析：覆盖度、变异测试分数、复杂度分析
同行评审：结构化的清单供同行验证

Examples

示例

BDD-Style Test Generation

BDD风格测试生成

See

modules/bdd-patterns.md

for additional patterns.

python

class TestGitWorkflow:
    """BDD-style tests for Git workflow operations."""

    def test_commit_workflow_with_staged_changes(self):
        """
        GIVEN a Git repository with staged changes
        WHEN the user runs the commit workflow
        THEN it should create a commit with proper message format
        AND all tests should pass
        """
        # Test implementation following TDD principles
        pass

Verification: Run

pytest -v

to verify tests pass.

更多模式详见

modules/bdd-patterns.md

。

python

class TestGitWorkflow:
    """针对Git工作流操作的BDD风格测试。"""

    def test_commit_workflow_with_staged_changes(self):
        """
        GIVEN 一个包含已暂存变更的Git仓库
        WHEN 用户运行提交工作流
        THEN 应创建一个符合规范格式的提交
        AND 所有测试均应通过
        """
        # 遵循TDD原则的测试实现
        pass

验证方式： 执行

pytest -v

确认测试通过。

Test Enhancement

测试优化

Add edge cases and error scenarios
Include performance benchmarks
Add mutation testing for robustness

See

modules/test-enhancement.md

for enhancement strategies.

添加边缘场景和错误场景
包含性能基准测试
增加变异测试以提升鲁棒性

优化策略详见

modules/test-enhancement.md

。

Integration with Existing Skills

与现有技能集成

git-workspace-review: Get context of changes
file-analysis: Understand code structure
test-driven-development: Apply strict TDD discipline
skills-eval: Validate quality and compliance

git-workspace-review：获取代码变更上下文
file-analysis：理解代码结构
test-driven-development：严格遵循TDD规范
skills-eval：验证质量与合规性

Success Metrics

成功指标

Test coverage > 85%
All tests follow BDD patterns
Zero broken tests in CI
Mutation score > 80%

测试覆盖度 > 85%
所有测试均遵循BDD模式
CI流水线中无失效测试
变异测试分数 > 80%

Troubleshooting FAQ

故障排查FAQ

Common Issues

常见问题

Q: Tests are failing after generation A: This is expected! The skill follows TDD principles - generated tests are designed to fail first. Follow the RED-GREEN-REFACTOR cycle:

Run the test and confirm it fails for the right reason
Implement minimal code to make it pass
Refactor for clarity

Q: Quality score is low despite having tests A: Check for these common issues:

Missing BDD patterns (Given/When/Then)
Vague assertions like
```
assert result is not None
```
Tests without documentation
Long, complex tests (>50 lines)

Q: Generated tests don't match my code structure A: The scripts analyze AST patterns and may need guidance:

Use
```
--style
```
flag to match your preferred BDD style
Check that source files have proper function/class definitions
Review the generated scaffolding and customize as needed

Q: Mutation testing takes too long A: Mutation testing is resource-intensive:

Use
```
--quick-mutation
```
flag for subset testing
Focus on critical modules first
Run overnight for detailed analysis

Q: Can't find tests for my file A: The analyzer uses naming conventions:

Source:
```
my_module.py
```
→ Test:
```
test_my_module.py
```
Check that test files follow pytest naming patterns
validate test directory structure is standard

问：生成测试后测试失败 答：这是正常现象！该技能遵循TDD原则——生成的测试设计为首先失败。请遵循RED-GREEN-REFACTOR周期：

运行测试并确认它因正确的原因失败
实现最小化代码使测试通过
重构代码以提升可读性

问：已有测试但质量分数较低 答：请检查以下常见问题：

缺少BDD模式（Given/When/Then）
模糊的断言，如
```
assert result is not None
```
测试无文档说明
冗长复杂的测试（超过50行）

问：生成的测试与我的代码结构不匹配 答：脚本会分析AST模式，可能需要一些引导：

使用
```
--style
```
参数匹配你偏好的BDD风格
确保源文件有正确的函数/类定义
查看生成的脚手架并按需自定义

问：变异测试耗时过长 答：变异测试资源消耗较大：

使用
```
--quick-mutation
```
参数进行子集测试
先聚焦于核心模块
运行整夜以进行精细化分析

问：找不到对应文件的测试 答：分析器使用命名约定：

源文件：
```
my_module.py
```
→ 测试文件：
```
test_my_module.py
```
确保测试文件遵循pytest命名模式
确认测试目录结构符合标准

Performance Tips

性能优化技巧

Large codebases: Use
```
--target
```
to focus on specific directories
CI integration: Run validation in parallel with other checks
Memory usage: Process files in batches for very large projects

大型代码库：使用
```
--target
```
参数聚焦于特定目录
CI集成：与其他检查并行运行验证
内存使用：处理超大型项目时分批处理文件

Getting Help

获取帮助

Check script outputs for detailed error messages
Use
```
--verbose
```
flag for more information
Review the validation report for specific recommendations
Start with small modules to understand patterns before scaling

查看脚本输出获取详细错误信息
使用
```
--verbose
```
参数获取更多信息
查看验证报告获取具体建议
先从小模块入手理解模式，再进行规模化使用

test-updates

Original

Translation

Table of Contents

目录

Test Updates and Maintenance

测试更新与维护

Overview

概述

Core Philosophy

核心理念

What It Is

功能介绍

Quick Start

快速开始

Quick Checklist for First Time Use

首次使用快速检查清单

detailed Test Update

全面测试更新

Run full test update workflow

运行完整的测试更新工作流

Targeted Test Updates

定向测试更新

Update tests for specific paths

更新特定路径下的测试

TDD for New Features

新功能的TDD实践

Apply TDD to new code

对新代码应用TDD

Using the Scripts Directly

直接使用脚本

Analyze test coverage gaps

分析测试覆盖缺口

Generate test scaffolding

生成测试脚手架

Check test quality

检查测试质量

Get JSON output for programmatic parsing - test_analyzer

获取用于程序化解析的JSON输出 - test_analyzer

Returns:

返回结果：

{

{

"success": true,

"success": true,

"data": {

"data": {

"source_files": ["src/module.py", ...],

"source_files": ["src/module.py", ...],

"test_files": ["tests/test_module.py", ...],

"test_files": ["tests/test_module.py", ...],

"uncovered_files": ["module_without_tests", ...],

"uncovered_files": ["module_without_tests", ...],

"coverage_gaps": [{"file": "...", "reason": "..."}]

"coverage_gaps": [{"file": "...", "reason": "..."}]

}

}

}

}

Get JSON output - test_generator

获取JSON输出 - test_generator

Returns:

返回结果：

{

{

"success": true,

"success": true,

"data": {

"data": {

"test_file": "path/to/test_my_module.py",

"test_file": "path/to/test_my_module.py",

"source_file": "src/my_module.py",

"source_file": "src/my_module.py",

"style": "pytest_bdd",

"style": "pytest_bdd",

"fixtures_included": true,

"fixtures_included": true,

"edge_cases_included": true,

"edge_cases_included": true,

"error_cases_included": true