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bug-reproduction-test-generator

@arabelatso · 收录于 1 周前

Automatically generates executable tests that reproduce reported bugs from issue reports and code repositories. Use when users need to: (1) Create a test that reproduces a bug described in an issue report, (2) Generate failing tests from bug descriptions, stack traces, or error messages, (3) Validate bug reports by creating reproducible test cases, (4) Convert issue reports into executable regression tests. Takes a repository and issue report as input and produces test code that reliably triggers the reported bug.

适合你,如果经常需要根据issue报告编写可复现bug的测试用例

/ 下载安装
bug-reproduction-test-generator.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add arabelatso/skills-4-se/bug-reproduction-test-generator
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- arabelatso/skills-4-se/bug-reproduction-test-generator
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify arabelatso/skills-4-se/bug-reproduction-test-generator
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

技能原文 SKILL.md作者撰写 · Apache-2.0 · 0f00a4f

Bug Reproduction Test Generator

Generate executable tests that reproduce reported bugs based on issue reports and code repositories.

Workflow

Follow these steps to generate a bug reproduction test:

1. Analyze the Issue Report

Extract key information from the issue report:

  • Symptoms: What goes wrong? (incorrect output, exception, crash, assertion failure, unexpected behavior)
  • Affected components: Which modules, classes, or functions are involved?
  • Triggering conditions: What inputs, states, or sequences trigger the bug?
  • Stack traces: If provided, identify the call chain and failure point
  • Expected vs. actual behavior: What should happen vs. what actually happens?
2. Inspect the Repository

Identify relevant code and context:

  • Locate the affected components mentioned in the issue
  • Find entry points (public APIs, main functions, test fixtures)
  • Understand dependencies and required setup
  • Identify the test framework used (pytest, unittest, JUnit, Jest, etc.)
  • Check existing test patterns for consistency
3. Generate the Reproduction Test

Create a minimal, focused test that:

Test structure:

  • Uses the repository's existing test framework and conventions
  • Sets up minimal preconditions needed to trigger the bug
  • Executes the code path that triggers the bug
  • Asserts the symptom described in the issue report

Assertions:

  • For exceptions: Assert the exception type and message match the report
  • For incorrect output: Assert actual output matches the reported incorrect behavior
  • For crashes: Assert the crash occurs at the expected point
  • For assertion failures: Reproduce the failing assertion

Documentation:

  • Add inline comments explaining the reproduction logic
  • Reference the issue number/URL in the test name or docstring
  • Document any assumptions made due to underspecified details
4. Output Format

Provide:

  1. Executable test code in the appropriate language and framework
  2. Inline comments explaining how the test reproduces the bug
  3. Markdown summary including:
  4. How the test reproduces the issue
  5. Which symptoms it validates
  6. Any assumptions made
  7. Instructions for running the test
Example Workflow

Issue Report:

Title: Division by zero in calculate_average()
Description: When calling calculate_average([]) with an empty list,
the function crashes with ZeroDivisionError instead of returning 0.

Stack trace:
  File "stats.py", line 15, in calculate_average
    return sum(values) / len(values)
ZeroDivisionError: division by zero

Generated Test (Python/pytest):

import pytest
from stats import calculate_average

def test_calculate_average_empty_list_reproduction():
    """
    Reproduces bug: calculate_average([]) raises ZeroDivisionError
    Issue: #123

    Expected: Should return 0 for empty list
    Actual: Raises ZeroDivisionError
    """
    # Trigger the bug with empty list input
    with pytest.raises(ZeroDivisionError):
        result = calculate_average([])

    # This test currently passes (reproduces the bug)
    # After fix, change to: assert calculate_average([]) == 0

Summary:

## Bug Reproduction Test

**Issue**: Division by zero in calculate_average()

**How it reproduces the bug:**
- Calls `calculate_average([])` with an empty list
- Asserts that ZeroDivisionError is raised (the buggy behavior)

**Symptoms validated:**
- Exception type: ZeroDivisionError
- Location: stats.py line 15

**Assumptions:**
- The function should return 0 for empty lists (common convention)

**Running the test:**

pytest test_stats.py::test_calculate_average_empty_list_reproduction

**After the bug is fixed:**
Replace the `pytest.raises` assertion with:

assert calculate_average([]) == 0


Language-Specific Patterns
Python (pytest/unittest)
import pytest

def test_bug_reproduction_issue_123():
    """Reproduces bug #123: [brief description]"""
    # Setup: Create conditions that trigger the bug

    # Execute: Run the code that exhibits the bug

    # Assert: Verify the buggy behavior occurs
    with pytest.raises(ExpectedException):
        buggy_function()
Java (JUnit)
@Test
public void testBugReproduction_Issue123() {
    // Reproduces bug #123: [brief description]

    // Setup: Create conditions that trigger the bug

    // Execute and Assert: Verify the buggy behavior
    assertThrows(ExpectedException.class, () -> {
        buggyMethod();
    });
}
JavaScript (Jest)
test('reproduces bug #123: [brief description]', () => {
  // Setup: Create conditions that trigger the bug

  // Execute and Assert: Verify the buggy behavior
  expect(() => {
    buggyFunction();
  }).toThrow(ExpectedException);
});
Constraints
  • Do not modify production code - Only create test code
  • Do not assume fixes - Test the buggy behavior, not the expected correct behavior (unless explicitly stated in the issue)
  • Document assumptions - If the issue is underspecified, state assumptions clearly
  • Prefer minimal tests - Focus on isolating the bug, avoid unnecessary setup
  • Match existing patterns - Follow the repository's test conventions and style
Handling Underspecified Issues

When the issue report lacks details:

  1. State assumptions explicitly in test comments
  2. Document what's unclear in the summary
  3. Provide multiple test variants if multiple interpretations are possible
  4. Ask clarifying questions if critical information is missing

Example:

def test_bug_reproduction_issue_456():
    """
    Reproduces bug #456: Null pointer exception in processData()

    ASSUMPTION: The bug occurs when input is null (not specified in issue)
    ASSUMPTION: Using default configuration (not specified in issue)
    """
    # Test with null input (assumed trigger)
    with pytest.raises(NullPointerException):
        processData(None)
Tips for Effective Reproduction Tests
  1. Start simple - Begin with the most direct path to trigger the bug
  2. Isolate the bug - Remove unrelated setup and assertions
  3. Make it deterministic - Avoid flaky conditions (timing, randomness)
  4. Reference the issue - Include issue number in test name and comments
  5. Verify it fails - Run the test to confirm it reproduces the bug
  6. Plan for the fix - Comment on how the test should change after the bug is fixed
按 Apache-2.0 许可原样转载,未经改动 · 在 GitHub 查看 →

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