refactor(topics): 멀티 에이전트용 지식 재편 — _Common(공통 기본기) + Domain_* 구조
에이전트 8종(대화형/프로그래머 C·S/디자이너/설계자/기획자/QA/PD/PM)에게 [공통 기본 능력 + 롤별 Specialty] 2층으로 지식을 주입하기 위한 재분류. 문서 내용·포맷은 무수정, 폴더 이동만 (6,372개 문서 수 보존 확인). - Topic_Programming → Domain_Programming (내부 구조 보존) - Topic_Graphic → Domain_Design - Topic_Business → Domain_Product - Topic_General → Domain_General - _Common 신설: Math(구 Topic_Math_Specialty), Reasoning(구 General/From_Thinking & Reasoning), Reasoning_Creativity(구 General/From_창의성), Communication(Poetic_Blog_Writing + From_writing) - 타 도메인의 From_* 폴더는 유지 (출처 표기일 뿐, 이미 도메인에 맞게 분류된 문서) - 빈 폴더 정리 (memory/procedures) - 에이전트→폴더 매핑은 workspace의 .astra/agent-knowledge-map.json (9개 에이전트) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Antigravity Agent
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---
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id: wiki-2026-0508-characterization-tests-특성화-테스트
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title: Characterization Tests (특성화 테스트)
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [Golden Master Tests, Approval Tests, Pinning Tests, Snapshot Tests]
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duplicate_of: none
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source_trust_level: A
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confidence_score: 0.9
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verification_status: applied
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tags: [testing, legacy-code, feathers, refactoring]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: typescript-python
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framework: jest-pytest-approvaltests
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---
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# Characterization Tests (특성화 테스트)
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## 매 한 줄
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> **"매 legacy code 의 actual behavior 의 capture — 매 spec 이 X, 매 photo 가 O."**. Michael Feathers 의 *Working Effectively with Legacy Code* (2004) 에서 정립. 매 untested legacy 의 refactoring 시작점. 매 "what should it do" X — 매 "what does it do right now" 의 lock down. 2026년 snapshot tests, ApprovalTests, golden master tests 모두 같은 family.
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## 매 핵심
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### 매 정의 (Feathers)
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> "A characterization test is a test that characterizes the actual behavior of a piece of code. There's no 'correct'... it just records what the system does."
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### 매 vs unit/spec test
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| 측면 | Spec Test | Characterization Test |
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|---|---|---|
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| Source of truth | Requirements / spec | Actual current behavior |
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| Failing means | Code has bug | Behavior changed (maybe intended) |
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| When to write | TDD, before code | Before refactoring legacy code |
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| Update on change | Fix code | Review diff, accept if intended |
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### 매 procedure (Feathers)
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1. Pick code 의 region.
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2. Write test 가 invokes the code with realistic inputs.
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3. Assert with **placeholder** (e.g. `assert result == "FILL_ME"`).
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4. Run, capture actual output.
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5. Replace placeholder with actual output.
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6. Now test pins behavior — refactor with confidence.
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### 매 variants
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- **Snapshot test** (Jest, Vitest): serialize output, compare next run.
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- **Approval test** (ApprovalTests): write to `.approved.txt`, manual review on diff.
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- **Golden master**: large input/output pair, often UI screenshot.
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- **Property-based regression**: random inputs, save outputs as golden.
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### 매 응용
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1. Refactoring legacy monolith without specs.
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2. Migration (framework upgrade, language port).
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3. Compiler / parser output stability.
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4. Report generation (PDFs, CSVs).
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5. UI visual regression (Percy, Chromatic).
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## 💻 패턴
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### Feathers procedure (TypeScript + Jest)
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```typescript
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import { calculateInvoice } from './legacy';
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describe('calculateInvoice — characterization', () => {
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it('records current behavior for typical input', () => {
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const result = calculateInvoice({
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items: [
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{ sku: 'A', qty: 2, price: 19.99 },
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{ sku: 'B', qty: 1, price: 5.00 },
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],
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customerType: 'premium',
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country: 'KR',
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});
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// Step 1: write `expect(result).toBe('PLACEHOLDER')`
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// Step 2: run, observe actual:
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// { subtotal: 44.98, discount: 4.50, vat: 4.05, total: 44.53 }
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// Step 3: paste it as expected
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expect(result).toEqual({
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subtotal: 44.98,
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discount: 4.50,
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vat: 4.05,
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total: 44.53,
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});
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});
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});
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```
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### Jest snapshot
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```typescript
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import { renderInvoiceHtml } from './render';
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test('invoice html — characterized', () => {
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const html = renderInvoiceHtml(SAMPLE_INVOICE);
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expect(html).toMatchSnapshot();
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});
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// First run: writes __snapshots__/invoice.test.ts.snap
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// Future runs: diffs. Use `--update-snapshot` after intentional change.
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```
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### ApprovalTests (Python)
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```python
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from approvaltests import verify
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def test_pdf_layout():
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pdf_text = render_pdf(sample_data)
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verify(pdf_text)
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# Writes `test_pdf_layout.received.txt`, compares to `.approved.txt`.
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# CI fails on diff; dev reviews then renames received→approved.
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```
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### Golden master with multiple inputs
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```python
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import json
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from pathlib import Path
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from legacy_pricing import compute_price
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def test_pricing_golden_master():
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cases = json.loads(Path("fixtures/cases.json").read_text())
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actual = [compute_price(c["input"]) for c in cases]
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expected = json.loads(Path("fixtures/expected.json").read_text())
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assert actual == expected
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```
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### Generating the golden initially
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```python
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# tools/regenerate_golden.py — run once, then commit
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import json
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from pathlib import Path
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from legacy_pricing import compute_price
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cases = json.loads(Path("fixtures/cases.json").read_text())
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out = [compute_price(c["input"]) for c in cases]
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Path("fixtures/expected.json").write_text(json.dumps(out, indent=2))
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```
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### Differential testing (old vs refactored)
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```typescript
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import { computePriceLegacy } from './pricing-legacy';
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import { computePriceNew } from './pricing-new';
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import fc from 'fast-check';
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test('refactor preserves behavior', () => {
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fc.assert(
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fc.property(
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fc.record({
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qty: fc.integer({ min: 1, max: 100 }),
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unitPrice: fc.float({ min: 0.01, max: 9999 }),
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}),
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(input) => {
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expect(computePriceNew(input))
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.toBeCloseTo(computePriceLegacy(input), 2);
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},
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),
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{ numRuns: 1000 },
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);
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});
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```
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### Capture I/O of legacy via instrumentation
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```python
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# Wrap legacy fn, log all inputs+outputs in production for a week,
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# then replay as test fixtures
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from functools import wraps
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import json, time
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def record(path):
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def deco(fn):
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@wraps(fn)
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def wrapper(*args, **kwargs):
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result = fn(*args, **kwargs)
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with open(path, "a") as f:
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f.write(json.dumps({
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"ts": time.time(),
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"args": args, "kwargs": kwargs,
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"result": result,
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}, default=str) + "\n")
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return result
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return wrapper
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return deco
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@record("fixtures/legacy_calls.jsonl")
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def legacy_compute(...): ...
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```
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## 매 결정 기준
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| 상황 | Approach |
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|---|---|
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| Pure function legacy | Inline assertion (Feathers procedure) |
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| Large structured output | Snapshot or ApprovalTests |
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| Visual UI | Storybook + Chromatic / Percy |
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| Two impls (refactor) | Differential testing + property-based |
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| Production behavior unknown | Record-replay from instrumentation |
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**기본값**: Snapshot test for serializable output, ApprovalTests for human-reviewed diffs (PDF, HTML), differential test during refactor.
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## 🔗 Graph
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- 변형: [[Approval Tests]]
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- 응용: [[Refactoring_Best_Practices|Refactoring]] · [[Visual Regression]]
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- Adjacent: [[Property-Based Testing]] · [[TDD]] · [[Test Doubles]]
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## 🤖 LLM 활용
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**언제**: legacy code refactor 시작, untested codebase 첫 test net, framework migration, output-shape stability (PDF/CSV/JSON).
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**언제 X**: greenfield TDD (use spec tests), rapidly evolving design (snapshots churn), security-critical (need real spec).
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## ❌ 안티패턴
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- **Treating snapshot as spec**: 매 snapshot fail — auto-update without review. 매 bug 의 silent merge.
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- **Huge unreadable snapshot**: 1000-line JSON — split into focused snapshots.
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- **No fixture review process**: golden master changes auto-merge — require reviewer.
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- **Characterization without refactor goal**: tests forever pin "legacy bug" 의 behavior — note bugs explicitly, fix later.
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- **Time/random in capture**: nondeterministic snapshots — freeze clock/seed.
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## 🧪 검증 / 중복
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- Verified (Feathers "Working Effectively with Legacy Code" 2004 / Jest docs / ApprovalTests / Beck "Test Driven Development").
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- 신뢰도 A.
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — Feathers procedure + snapshot/approval/differential 패턴 |
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