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property-based-testing基于属性的测试

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。

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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:property-based-testing(基于属性的测试)
来源仓库:https://github.com/laurigates/claude-plugins
仓库路径:skills/property-based-testing
安装命令:
npx skills add https://github.com/laurigates/claude-plugins --skill property-based-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/laurigates/claude-plugins --skill property-based-testing

简介

property-based-testing 用于辅助测试设计、自动化测试和用例整理。

  • 适合编写单元测试、端到端测试或根据日志定位问题。
  • 使用时需确认测试框架、运行命令和夹具数据,避免误改逻辑。
  • 涉及浏览器或外部服务时,应区分本地模拟与生产环境。
  • 确保测试目标真实有效,不为了通过而破坏原有功能。

SKILL.md

Property-Based Testing

Expert knowledge for property-based testing - automatically generating test cases to verify code properties rather than testing specific examples.

When to Use This Skill

Use this skill when...Use another skill instead when...
Testing mathematical properties (commutative, associative)Writing specific example-based unit tests
Testing encode/decode roundtripsSetting up test runner configuration
Finding edge cases automaticallyDoing E2E browser testing
Validating data transformations and invariantsAnalyzing test quality or smells
Testing API contracts with generated dataRunning mutation testing

Core Expertise

Property-Based Testing Concept

  • Traditional testing: Test specific examples
  • Property-based testing: Test properties that should hold for all inputs
  • Generators: Automatically create diverse test inputs
  • Shrinking: Minimize failing cases to simplest example
  • Coverage: Explore edge cases humans might miss

When to Use Property-Based Testing

  • Mathematical operations (commutative, associative properties)
  • Encoders/decoders (roundtrip properties)
  • Parsers and serializers
  • Data transformations
  • API contracts
  • Invariants and constraints

TypeScript/JavaScript (fast-check)

Installation

# Using Bun
bun add -d fast-check

# Using npm
npm install -D fast-check

Basic Example

import { test } from 'vitest'
import * as fc from 'fast-check'

// Property-based test
test('reverse twice returns original - property based', () => {
  fc.assert(
    fc.property(
      fc.array(fc.integer()), // Generate random arrays of integers
      (arr) => {
        expect(reverse(reverse(arr))).toEqual(arr)
      }
    )
  )
})
// fast-check automatically generates 100s of test cases!

Key Generators (Quick Reference)

GeneratorDescription
fc.integer()Any integer (with optional min/max)
fc.nat()Natural numbers (>= 0)
fc.float() / fc.double()Floating-point numbers
fc.string()Any string (with optional length)
fc.emailAddress()Email format strings
fc.array(arb)Arrays of arbitrary type
fc.record({...})Object with typed fields
fc.boolean()Boolean values
fc.constantFrom(...)Pick from options
fc.tuple(...)Fixed-size tuples
fc.oneof(...)Union types
fc.option(arb)Value or null
fc.date()Date objects

Common Properties to Test

PropertyPatternExample
Roundtripf(g(x)) = xencode/decode, serialize/parse
Idempotencef(f(x)) = f(x)sort, normalize, format
Commutativityf(a,b) = f(b,a)add, merge, union
Associativityf(f(a,b),c) = f(a,f(b,c))add, concat
Identityf(x, id) = xmultiply by 1, add 0
Inversef(g(x)) = xencrypt/decrypt

Configuration

fc.assert(property, {
  numRuns: 1000,      // Run 1000 tests (default: 100)
  seed: 42,           // Reproducible tests
  endOnFailure: true, // Stop after first failure
})

Preconditions

fc.pre(b !== 0) // Skip cases where b is 0

Python (Hypothesis)

Installation

# Using uv
uv add --dev hypothesis

# Using pip
pip install hypothesis

Basic Example

from hypothesis import given, strategies as st

@given(st.lists(st.integers()))
def test_reverse_twice_property(arr):
    assert reverse(reverse(arr)) == arr
    # Hypothesis automatically generates 100s of test cases!

Key Strategies (Quick Reference)

StrategyDescription
st.integers()Any integer (with optional bounds)
st.floats()Floating-point numbers
st.text()Any string (with optional size)
st.binary()Byte strings
st.lists(strat)Lists of given strategy
st.sets(strat)Unique value sets
st.dictionaries(k, v)Dictionaries
st.booleans()Boolean values
st.sampled_from(...)Pick from options
st.tuples(...)Fixed-size tuples
st.one_of(...)Union types
st.dates() / st.datetimes()Date/time values
st.builds(Class,...)Build objects from strategies

Configuration

from hypothesis import given, settings, strategies as st

@settings(max_examples=1000, deadline=None)
@given(st.lists(st.integers()))
def test_with_custom_settings(arr):
    assert sort(arr) == sorted(arr)

Assumptions

from hypothesis import assume
assume(b != 0)  # Skip cases where b is 0

Stateful Testing

Hypothesis supports stateful testing via RuleBasedStateMachine for testing sequences of operations against invariants.

Agentic Optimizations

ContextCommand
Quick TS testbunx vitest --dots --bail=1 --grep 'property'
Quick Python testuv run pytest -x -q --tb=short -k 'property'
CI TS testbunx vitest run --reporter=junit --grep 'property'
CI Python testuv run pytest --hypothesis-show-statistics -q
Reproduciblefc.assert(prop, {seed: 42}) or @settings(derandomize=True)
Fast iterationfc.assert(prop, {numRuns: 50}) or @settings(max_examples=50)

For detailed examples, advanced patterns, and best practices, see REFERENCE.md.

See Also

  • vitest-testing - Unit testing framework
  • python-testing - Python pytest testing
  • test-quality-analysis - Detecting test smells
  • mutation-testing - Validate test effectiveness

References

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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

34.17%
按下载量换算157

Claude

29.99%
按下载量换算138

Cursor

19.99%
按下载量换算92

Gemini CLI

10.6%
按下载量换算49

安全审计

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