golden-path-testing

name	golden-path-testing
description	Design golden path tests that validate critical user journeys end-to-end. Outputs journey mapping, test scope decisions, data strategy, and reliability patterns.
argument-hint	["critical user journeys","tech stack","test framework","environment access"]
allowed-tools	Read, Write

Golden Path Testing

Golden path tests validate the most critical user journeys — the paths that must work for the business to function. Unlike comprehensive E2E tests, golden path tests are intentionally narrow: they cover the core happy paths that, if broken, cause immediate revenue or user impact. They run frequently and must be highly reliable.

Identifying Golden Paths

## Selection Criteria

A journey qualifies as a golden path if:
1. It generates significant revenue or drives core business value
2. Breaking it would cause immediate user-visible impact
3. It is frequently used (top N% by volume)
4. Its failure would require P1 incident response

## Example Golden Paths by Product Type

E-commerce:
  ✓ Search → Product Page → Add to Cart → Checkout → Order Confirmation
  ✓ Login → View Order History → Track Order
  ✗ Browse related products (nice to have, not revenue-critical)

SaaS:
  ✓ Sign Up → First Workspace → Create First Project → Invite Teammate
  ✓ Login → Create Report → Export → Share
  ✗ Customise profile photo (not revenue-critical)

Banking:
  ✓ Login (with MFA) → Check Balance → Transfer Funds
  ✓ Login → Pay Bill → Confirm Payment
  ✗ Download 2-year statement (infrequent; not critical)

Golden Path Test Design

import pytest
from playwright.sync_api import Page, expect

class TestCheckoutGoldenPath:
    """The single most critical user journey — must always pass."""

    @pytest.fixture(autouse=True)
    def setup(self, page: Page, base_url: str):
        self.page = page
        self.base_url = base_url

    def test_complete_purchase_flow(self):
        """
        Golden Path: Guest checkout — product to order confirmation.
        If this fails, revenue generation is impaired.
        SLA: Must pass 99.9% of runs (max 1 failure per 1000).
        """
        page = self.page

        # Step 1: Search for product
        page.goto(f"{self.base_url}/")
        page.fill('[data-testid="search-input"]', "blue widget")
        page.press('[data-testid="search-input"]', "Enter")
        expect(page.locator('[data-testid="product-card"]').first).to_be_visible(timeout=5000)

        # Step 2: View product
        page.locator('[data-testid="product-card"]').first.click()
        expect(page.locator('[data-testid="product-title"]')).to_be_visible()
        expect(page.locator('[data-testid="price"]')).to_contain_text("$")

        # Step 3: Add to cart
        page.click('[data-testid="add-to-cart"]')
        expect(page.locator('[data-testid="cart-count"]')).to_have_text("1")

        # Step 4: Checkout
        page.click()
        page.fill(, )
        page.fill(, )
        page.fill(, )
        page.fill(, )
        page.click()

        
        expect(page.locator()).to_be_visible(timeout=)
        order_id = page.locator().text_content()
         order_id, 

Golden Path Reliability Requirements

# Golden path tests must be held to higher reliability standards
# than regular E2E tests — they must almost never fail due to test issues

# Reliability patterns:
class ReliableStep:
    MAX_RETRIES = 3
    RETRY_DELAY_MS = 500

    @staticmethod
    def click_with_retry(page, selector: str):
        """Retry click for transient DOM timing issues."""
        for attempt in range(ReliableStep.MAX_RETRIES):
            try:
                page.locator(selector).click(timeout=5000)
                return
            except Exception as e:
                if attempt == ReliableStep.MAX_RETRIES - 1:
                    raise
                page.wait_for_timeout(ReliableStep.RETRY_DELAY_MS)

    @staticmethod
    def fill_with_retry(page, selector: str, value: str):
        page.locator(selector).fill("")  # Clear first
        page.locator(selector).fill(value)
        # Verify the value was entered correctly
        actual = page.locator(selector).input_value()
        assert actual == value, f"Failed to fill {selector}: expected {value!r}, got {actual!r}"

Data Strategy for Golden Path Tests

## Test Data Approaches

APPROACH 1: Dedicated Test Accounts
  Pros: Stable; no interference with real users
  Cons: Test data accumulates; accounts may expire
  Pattern:
    - Pre-created accounts: [e-mail]
    - Reset state before each run via API
    - Separate test product catalog (real prices, fake inventory)

APPROACH 2: Generated Data per Run
  Pros: No state accumulation; fully isolated
  Cons: Slower; more setup
  Pattern:
    - Create test user via API (not UI)
    - Use `testuser+<uuid>@company.com` email pattern
    - Clean up after test (or let TTL expire)

APPROACH 3: Fixture Data (Recommended for Speed)
  Pros: Fast; predictable
  Cons: Must maintain fixture state
  Pattern:
    - Database seed applied before test run
    - Test uses known fixture IDs
    - Transaction rollback after test

## What NOT to Use
  - Production user accounts (GDPR, data contamination)
  - Real payment credentials (use test card numbers: 4242 4242 4242 4242)
  - Real email addresses (use `@goldenpath.invalid` domain)

CI Configuration for Golden Paths

# Golden path tests: run frequently, fast feedback
- name: Golden Path Tests
  run: pytest tests/golden_path/ -v --timeout=60
  env:
    BASE_URL: https://staging.example.com
    HEADLESS: "true"
  # Run on every merge to main AND every 15 minutes in production (synthetic monitoring)

# Alert when golden path fails
- name: Alert on failure
  if: failure()
  run: |
    curl -X POST $SLACK_WEBHOOK_URL       -d '{"text": "GOLDEN PATH FAILURE on ${{ github.ref }}: ${{ github.run_url }}"}'

Anti-Patterns to Avoid

Anti-Pattern	Problem	Fix
Too many golden paths	Suite becomes slow; flaky	Max 5-10 golden paths per product area
Testing edge cases in golden path	Slow; defeats the purpose	Golden path = happy path only
No SLA for golden path reliability	Flakiness tolerated	<0.1% failure rate from test issues required
Production data in tests	GDPR; data contamination	Dedicated test accounts or synthetic data
Only running on PR	Production can degrade between PRs	Run on schedule (every 15 min) as synthetic monitoring

10 Rules

1. Golden paths cover the 5-10 journeys that, if broken, cause immediate revenue or user impact.
2. Golden path tests are always happy path — no edge cases, no error conditions.
3. Reliability SLA is stricter than regular E2E: <0.1% failure rate from test infrastructure.
4. Golden path tests run on every merge to main AND on a schedule in production.
5. Failures alert immediately — not as a daily digest.
6. Test data is isolated: dedicated test accounts, test payment credentials, synthetic emails.
7. Each test is independent — no shared state or ordering dependencies.
8. Golden path scope is deliberately narrow — resist adding assertions "while we're there."
9. Execution time matters: each golden path test under 60 seconds.
10. Golden path failures are P1 until proven to be test infrastructure issues.