2nd/10_Wiki/Topics/Architecture/하향식_탐색_Top-Down_Approach.md

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id	title	category	status	canonical_id	aliases	duplicate_of	source_trust_level	confidence_score	verification_status	tags	raw_sources	last_reinforced	github_commit	tech_stack
wiki-2026-0508-하향식-탐색-top-down-approach	하향식 탐색 Top-Down Approach	10_Wiki/Topics	verified	self	Top-Down Design Stepwise Refinement 하향식 설계	none	A	0.9	applied	architecture design-method decomposition		2026-05-10	pending	language framework language-agnostic design-method

하향식 탐색 (Top-Down Approach)

매 한 줄

"매 큰 그림 → 매 세부". 매 system 의 high-level abstraction 부터 시작 → 매 단계마다 decomposition. 매 1970s Niklaus Wirth 의 stepwise refinement 가 origin — 매 modern 2026 microservice / DDD 의 strategic design 까지 매 살아있는 design heuristic.

매 핵심

매 핵심 idea

• 매 추상 → 매 구체: System 전체 → subsystems → modules → functions → lines.
• 매 deferred decision: Lower-level detail 의 결정 의 미루기 — 매 abstraction barrier.
• 매 wishful thinking: 매 "이 helper 가 있다 가정" → 매 나중에 implement.

매 vs Bottom-Up

• Top-Down: 매 unknown / new system 의 design 적합. 매 risk: leaf-level 에서 매 mismatch 발견.
• Bottom-Up: 매 reusable primitive 부터. 매 known domain (e.g. data pipeline) 적합.
• 매 실전: 매 hybrid (meet-in-middle) 의 default.

매 응용

1. DDD strategic design — bounded context → context map → aggregate.
2. Microservice decomposition — capability mapping → service boundary.
3. Functional decomposition — main() → step functions → primitives.

💻 패턴

Stepwise refinement (pseudocode → real)

# Level 0: intent
def process_orders():
    """Process today's orders end-to-end."""

# Level 1: high-level steps
def process_orders():
    orders = fetch_pending_orders()
    validated = [o for o in orders if validate(o)]
    results = [charge_and_ship(o) for o in validated]
    notify_customers(results)

# Level 2: implement leaves (deferred until now)
def fetch_pending_orders() -> list[Order]:
    return db.query(Order).filter(Order.status == "pending").all()

Wishful thinking — assume helpers exist

def render_dashboard(user_id: str) -> HTML:
    user = fetch_user(user_id)              # assume
    metrics = compute_metrics(user)         # assume
    chart = build_chart(metrics)            # assume
    return layout(header(user), chart)      # assume
# 매 implement leaves 의 last.

DDD top-down decomposition

Bounded Context: Order Management
  ├─ Aggregate: Order
  │   ├─ Entity: OrderLine
  │   └─ Value Object: Money, Address
  ├─ Aggregate: Cart
  └─ Domain Service: Pricing

Microservice capability decomposition

# top-down: business capability → service
Capability: Checkout
  Sub-capability: Cart Management   → cart-service
  Sub-capability: Payment           → payment-service
  Sub-capability: Order Persistence → order-service
  Sub-capability: Notification      → notification-service

Test-first top-down (London-school TDD)

def test_charge_order_calls_gateway(mocker):
    gateway = mocker.Mock()
    repo = mocker.Mock()
    svc = OrderService(gateway, repo)         # 매 collaborator 추측
    svc.charge(Order(id=1, total=100))
    gateway.charge.assert_called_once_with(100)
# 매 mock 의 design 의 driver — 매 collaborator interface 의 top-down emerge.

Recursive descent parser (top-down classic)

def parse_expr(tokens):
    left = parse_term(tokens)
    while tokens.peek() in ("+", "-"):
        op = tokens.next()
        right = parse_term(tokens)
        left = BinOp(op, left, right)
    return left

def parse_term(tokens):
    left = parse_factor(tokens)
    # ...

매 결정 기준

상황	Approach
Greenfield, unknown domain	Top-Down (explore via decomposition)
Known primitives, integration heavy	Bottom-Up
Library 의 design	Bottom-Up (primitive first)
Application / product 의 design	Top-Down → Hybrid
Refactor existing code	Inside-Out (seam first)

기본값: Top-Down 으로 strategy → bottom-up primitive 의 meet-in-middle.

🔗 Graph

• 부모: 아키텍처 패턴 지식 · 객체 지향 소프트웨어 아키텍처 설계
• 변형: Bottom Up Approach
• 응용: DDD · Hexagonal_Architecture · Refactoring Techniques (리팩토링 기법)
• Adjacent: 추상화(Abstraction) · High-Cohesion-Low-Coupling

🤖 LLM 활용

언제: 매 새로운 system 의 design 의 시작, 매 unknown domain 의 explore, 매 architectural conversation 의 frame. 언제 X: 매 well-known primitive 의 mechanical assembly, 매 retrofit / legacy refactor (seam-first 가 더 안전).

❌ 안티패턴

• Pseudocode 가 implementation 화: 매 leaf 의 implement 안 함. 매 wishful 의 영원히 wish.
• Premature decomposition: 매 너무 일찍 fix layer boundary → 매 나중에 leaky.
• No bottom check: 매 leaf primitive 가 매 expressible 인지 verify 안 함 → 매 mismatch.

🧪 검증 / 중복

• Verified (Wirth 1971 "Program Development by Stepwise Refinement"; Evans DDD 2003).
• 신뢰도 A.

🕓 Changelog

날짜	변경
2026-05-08	Phase 1
2026-05-10	Manual cleanup — top-down 의 stepwise refinement / wishful thinking / DDD-microservice 의 application