domain-driven-design

name

domain-driven-design

description

Domain-Driven Design system for software development. Use when designing new systems with DDD principles, refactoring existing codebases toward DDD, generating code scaffolding (entities, aggregates, repositories, domain events), facilitating Event Storming sessions, creating bounded context maps, or performing code reviews with a DDD lens. Covers both strategic design (bounded contexts, subdomains, context maps, ubiquitous language) and tactical design (entities, value objects, aggregates, domain services, repositories). Supports all major architecture patterns (Hexagonal/Ports & Adapters, CQRS, Event Sourcing, Clean Architecture) with language-agnostic guidance and concrete examples in Python and TypeScript.

Domain-Driven Design Skill

Apply DDD to build software that reflects deep understanding of the business domain.

Quick Reference

Task	Reference
Bounded contexts, subdomains, context maps	strategic-design.md
Entities, value objects, aggregates, repositories	tactical-design.md
Hexagonal, CQRS, Event Sourcing, Clean Architecture	architecture-patterns.md
Event Storming facilitation & documentation	event-storming.md
Python implementations (Pydantic, SQLAlchemy, FastAPI)	python-patterns.md
TypeScript implementations (NestJS, TypeORM, Prisma)	typescript-patterns.md
DDD code review criteria	code-review.md

Core Workflow

1. Identify the Task Type

Designing new system? → Start with strategic design, then tactical Refactoring existing code? → Assess current state, identify bounded contexts, refactor incrementally Generating scaffolding? → Determine patterns needed, generate code Event Storming? → Follow facilitation guide Code review? → Apply DDD checklist

2. Strategic Before Tactical

Always establish strategic design first:

1. Identify subdomains (Core, Supporting, Generic)
2. Define bounded contexts and their boundaries
3. Map context relationships (upstream/downstream, conformist, ACL, etc.)
4. Establish ubiquitous language per context

3. Select Architecture Pattern

Choose based on domain complexity and requirements:

Pattern	When to Use
Layered	Simple CRUD, low complexity
Hexagonal	Need to isolate domain from infrastructure
Clean Architecture	Complex business rules, multiple delivery mechanisms
CQRS	Different read/write models, complex queries
Event Sourcing	Audit trail required, temporal queries, event-driven

Patterns can be combined (e.g., Hexagonal + CQRS + Event Sourcing).

4. Apply Tactical Patterns

Select tactical building blocks based on needs:

Building Block	Purpose
Entity	Identity matters, mutable, lifecycle
Value Object	Defined by attributes, immutable, no identity
Aggregate	Consistency boundary, transactional unit
Domain Service	Stateless operations spanning multiple aggregates
Repository	Collection-like interface for aggregate persistence
Domain Event	Record of something significant that happened
Factory	Complex object creation logic
Specification	Encapsulated business rules for querying/validation

5. Implementation Guidelines

General principles:

• Domain layer has ZERO infrastructure dependencies
• Depend on abstractions (interfaces/protocols), not concretions
• One aggregate = one repository = one transaction
• Aggregates reference other aggregates by ID only
• Validate invariants within aggregate boundaries
• Use domain events for cross-aggregate communication

Language selection:

• Read python-patterns.md for Python with Pydantic, SQLAlchemy, FastAPI
• Read typescript-patterns.md for TypeScript with NestJS, TypeORM, Prisma

Project Structure Template

src/
├── domain/                    # Pure domain logic (no dependencies)
│   ├── model/                 # Entities, Value Objects, Aggregates
│   ├── service/               # Domain Services
│   ├── event/                 # Domain Events
│   ├── repository/            # Repository interfaces (ports)
│   └── specification/         # Business rule specifications
├── application/               # Use cases, orchestration
│   ├── command/               # Command handlers (write)
│   ├── query/                 # Query handlers (read)
│   ├── dto/                   # Data transfer objects
│   └── service/               # Application services
├── infrastructure/            # External concerns
│   ├── persistence/           # Repository implementations
│   ├── messaging/             # Event bus, message queue
│   └── external/              # Third-party integrations
└── interface/                 # Delivery mechanisms
    ├── api/                   # REST/GraphQL controllers
    ├── cli/                   # Command-line interface
    └── event/                 # Event consumers

Anti-Patterns to Avoid

• Anemic Domain Model: Entities with only getters/setters, logic in services
• God Aggregate: Too many entities in one aggregate
• Shared Kernel Abuse: Overusing shared code between contexts
• Infrastructure Leak: Database concerns in domain layer
• Missing Ubiquitous Language: Technical terms instead of domain terms
• Aggregate Reference by Object: Should reference by ID only
• Transaction Across Aggregates: Violates consistency boundaries

When NOT to Use DDD

DDD adds complexity. Avoid for:

• Simple CRUD applications
• Technical/infrastructure projects without complex business logic
• Prototypes or throwaway code
• Teams unfamiliar with the domain (learn domain first)

Use DDD when:

• Complex, evolving business logic
• Long-lived systems requiring maintainability
• Multiple teams working on related domains
• Domain experts available for collaboration