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E2E 테스트

Playwright E2E 테스트 패턴, 페이지 객체 모델, 설정, CI/CD 통합, 아티팩트 관리 및 불안정한 테스트 전략을 다룹니다. Playwright 테스트를 작성하거나, 페이지 객체를 구성하거나, CI에서 불안정한 E2E 실행을 수정할 때 사용하세요.

E2E 테스트란 무엇인가요?

이 기술은 안정적이고 빠르며 유지보수 가능한 E2E 테스트 스위트를 구축하기 위한 종합적인 Playwright 패턴 모음입니다. 페이지 객체 모델(POM)을 사용하여 테스트 코드와 페이지 상호작용을 분리하고, 재사용성과 가독성을 높입니다. 테스트 구성, 불안정한 테스트 처리(격리, 조건부 건너뛰기), 스크린샷, 트레이스, 비디오와 같은 아티팩트 관리, GitHub Actions 기반 CI/CD 통합, E2E 테스트 보고서 템플릿을 포함합니다. 또한 Wallet/Web3 연결 및 금융/중요 흐름 테스트에 대한 구체적인 지침을 제공하여, 실제 자산을 다루는 애플리케이션의 안전한 테스트를 지원합니다. 이 기술은 Claude Code, Cursor, Codex와 같은 AI 에이전트와 함께 사용할 수 있습니다.

지원 대상~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/e2e-testing

즐겨 사용하는 AI에게 물어보기

이 에이전트 스킬이 미리 로드된 새 채팅을 엽니다.

문서

E2E 테스트 패턴

안정적이고 빠르며 유지보수 가능한 E2E 테스트 스위트를 구축하기 위한 종합적인 Playwright 패턴입니다.

테스트 파일 구성

tests/
├── e2e/
│   ├── auth/
│   │   ├── login.spec.ts
│   │   ├── logout.spec.ts
│   │   └── register.spec.ts
│   ├── features/
│   │   ├── browse.spec.ts
│   │   ├── search.spec.ts
│   │   └── create.spec.ts
│   └── api/
│       └── endpoints.spec.ts
├── fixtures/
│   ├── auth.ts
│   └── data.ts
└── playwright.config.ts

페이지 객체 모델 (POM)

import { Page, Locator } from '@playwright/test'

export class ItemsPage {
  readonly page: Page
  readonly searchInput: Locator
  readonly itemCards: Locator
  readonly createButton: Locator

  constructor(page: Page) {
    this.page = page
    this.searchInput = page.locator('[data-testid="search-input"]')
    this.itemCards = page.locator('[data-testid="item-card"]')
    this.createButton = page.locator('[data-testid="create-btn"]')
  }

  async goto() {
    await this.page.goto('/items')
    await this.page.waitForLoadState('networkidle')
  }

  async search(query: string) {
    await this.searchInput.fill(query)
    await this.page.waitForResponse(resp => resp.url().includes('/api/search'))
    await this.page.waitForLoadState('networkidle')
  }

  async getItemCount() {
    return await this.itemCards.count()
  }
}

테스트 구조

import { test, expect } from '@playwright/test'
import { ItemsPage } from '../../pages/ItemsPage'

test.describe('아이템 검색', () => {
  let itemsPage: ItemsPage

  test.beforeEach(async ({ page }) => {
    itemsPage = new ItemsPage(page)
    await itemsPage.goto()
  })

  test('키워드로 검색 가능', async ({ page }) => {
    await itemsPage.search('test')

    const count = await itemsPage.getItemCount()
    expect(count).toBeGreaterThan(0)

    await expect(itemsPage.itemCards.first()).toContainText(/test/i)
    await page.screenshot({ path: 'artifacts/search-results.png' })
  })

  test('검색 결과 없음 처리', async ({ page }) => {
    await itemsPage.search('xyznonexistent123')

    await expect(page.locator('[data-testid="no-results"]')).toBeVisible()
    expect(await itemsPage.getItemCount()).toBe(0)
  })
})

Playwright 구성

import { defineConfig, devices } from '@playwright/test'

export default defineConfig({
  testDir: './tests/e2e',
  fullyParallel: true,
  forbidOnly: !!process.env.CI,
  retries: process.env.CI ? 2 : 0,
  workers: process.env.CI ? 1 : undefined,
  reporter: [
    ['html', { outputFolder: 'playwright-report' }],
    ['junit', { outputFile: 'playwright-results.xml' }],
    ['json', { outputFile: 'playwright-results.json' }]
  ],
  use: {
    baseURL: process.env.BASE_URL || 'http://localhost:3000',
    trace: 'on-first-retry',
    screenshot: 'only-on-failure',
    video: 'retain-on-failure',
    actionTimeout: 10000,
    navigationTimeout: 30000,
  },
  projects: [
    { name: 'chromium', use: { ...devices['Desktop Chrome'] } },
    { name: 'firefox', use: { ...devices['Desktop Firefox'] } },
    { name: 'webkit', use: { ...devices['Desktop Safari'] } },
    { name: 'mobile-chrome', use: { ...devices['Pixel 5'] } },
  ],
  webServer: {
    command: 'npm run dev',
    url: 'http://localhost:3000',
    reuseExistingServer: !process.env.CI,
    timeout: 120000,
  },
})

불안정한 테스트 패턴

격리

test('flaky: 복잡한 검색', async ({ page }) => {
  test.fixme(true, '불안정 - Issue #123')
  // 테스트 코드...
})

test('조건부 건너뛰기', async ({ page }) => {
  test.skip(process.env.CI, 'CI에서 불안정 - Issue #123')
  // 테스트 코드...
})

불안정성 식별

npx playwright test tests/search.spec.ts --repeat-each=10
npx playwright test tests/search.spec.ts --retries=3

일반적인 원인 및 해결책

경쟁 조건:

// 나쁨: 요소가 준비되었다고 가정
await page.click('[data-testid="button"]')

// 좋음: 자동 대기 로케이터 사용
await page.locator('[data-testid="button"]').click()

네트워크 타이밍:

// 나쁨: 임의 타임아웃
await page.waitForTimeout(5000)

// 좋음: 특정 조건 대기
await page.waitForResponse(resp => resp.url().includes('/api/data'))

애니메이션 타이밍:

// 나쁨: 애니메이션 중 클릭
await page.click('[data-testid="menu-item"]')

// 좋음: 안정화 대기
await page.locator('[data-testid="menu-item"]').waitFor({ state: 'visible' })
await page.waitForLoadState('networkidle')
await page.locator('[data-testid="menu-item"]').click()

아티팩트 관리

스크린샷

await page.screenshot({ path: 'artifacts/after-login.png' })
await page.screenshot({ path: 'artifacts/full-page.png', fullPage: true })
await page.locator('[data-testid="chart"]').screenshot({ path: 'artifacts/chart.png' })

트레이스

await browser.startTracing(page, {
  path: 'artifacts/trace.json',
  screenshots: true,
  snapshots: true,
})
// ... 테스트 액션 ...
await browser.stopTracing()

비디오

// playwright.config.ts
use: {
  video: 'retain-on-failure',
  videosPath: 'artifacts/videos/'
}

CI/CD 통합

# .github/workflows/e2e.yml
name: E2E 테스트
on: [push, pull_request]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: 20
      - run: npm ci
      - run: npx playwright install --with-deps
      - run: npx playwright test
        env:
          BASE_URL: ${{ vars.STAGING_URL }}
      - uses: actions/upload-artifact@v4
        if: always()
        with:
          name: playwright-report
          path: playwright-report/
          retention-days: 30

테스트 보고서 템플릿

# E2E 테스트 보고서

**날짜:** YYYY-MM-DD HH:MM
**소요 시간:** Xm Ys
**상태:** 통과 / 실패

## 요약
- 전체: X | 통과: Y (Z%) | 실패: A | 불안정: B | 건너뜀: C

## 실패한 테스트

### test-name
**파일:** `tests/e2e/feature.spec.ts:45`
**오류:** 예상 요소가 보이지 않음
**스크린샷:** artifacts/failed.png
**권장 수정:** [설명]

## 아티팩트
- HTML 보고서: playwright-report/index.html
- 스크린샷: artifacts/*.png
- 비디오: artifacts/videos/*.webm
- 트레이스: artifacts/*.zip

Wallet / Web3 테스트

test('지갑 연결', async ({ page, context }) => {
  // 지갑 제공자 모의
  await context.addInitScript(() => {
    window.ethereum = {
      isMetaMask: true,
      request: async ({ method }) => {
        if (method === 'eth_requestAccounts')
          return ['0x1234567890123456789012345678901234567890']
        if (method === 'eth_chainId') return '0x1'
      }
    }
  })

  await page.goto('/')
  await page.locator('[data-testid="connect-wallet"]').click()
  await expect(page.locator('[data-testid="wallet-address"]')).toContainText('0x1234')
})

금융 / 중요 흐름 테스트

test('거래 실행', async ({ page }) => {
  // 프로덕션 건너뛰기 — 실제 자금
  test.skip(process.env.NODE_ENV === 'production', '프로덕션에서 건너뜀')

  await page.goto('/markets/test-market')
  await page.locator('[data-testid="position-yes"]').click()
  await page.locator('[data-testid="trade-amount"]').fill('1.0')

  // 미리보기 확인
  const preview = page.locator('[data-testid="trade-preview"]')
  await expect(preview).toContainText('1.0')

  // 확인 후 블록체인 대기
  await page.locator('[data-testid="confirm-trade"]').click()
  await page.waitForResponse(
    resp => resp.url().includes('/api/trade') && resp.status() === 200,
    { timeout: 30000 }
  )

  await expect(page.locator('[data-testid="trade-success"]')).toBeVisible()
})

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/ECC

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

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