nWave/skills/nw-ddd-strategic/SKILL.md
Strategic DDD — bounded context discovery, context mapping patterns, subdomain classification, ubiquitous language, and organizational alignment
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Domain discovery and boundary definition at the organizational level. Strategic DDD answers: "Where are the boundaries?" and "How do contexts relate?"
Subdomains exist in the problem space. Classify before modeling.
| Type | Competitive advantage | Build or buy | DDD investment | Staffing | |------|----------------------|--------------|----------------|----------| | Core | Yes, unique differentiator | Build in-house | Full strategic + tactical | Senior talent | | Supporting | No, enables core | Build (simplified) or outsource | Pragmatic tactical | Mid-level | | Generic | No, commodity | Buy/integrate (Stripe, Auth0) | Minimal/none | Junior/integration |
Decision heuristic: If two competitors solve this the same way, it's Generic. If your approach gives you an edge, it's Core. Everything else is Supporting.
A bounded context is a software boundary within which a model is consistent. Different from subdomains (problem-space). They should align but are independent concepts.
Language divergence (primary signal): When the same word means different things to different groups, you've found a boundary. "Account" in billing vs. "Account" in identity. "Product" in catalog vs. "Product" in inventory.
Organizational structure: Teams that communicate frequently often share a context. Teams with formal handoffs often have separate contexts. Conway's Law applies.
Consistency requirements: Where true invariants must be maintained transactionally defines aggregate boundaries, which cluster into contexts.
EventStorming Big Picture: Domain events placed on timeline. When events cluster into distinct swimlanes with different actors and vocabulary, those are context candidates.
Domain Storytelling: Actors perform activities on work objects. When actors, activities, or work objects change meaning, you've crossed a boundary.
Nine patterns describing how bounded contexts relate. Draw the context map before writing code.
Partnership: Two contexts evolve together. Both teams coordinate releases. Use when: genuinely reciprocal dependency, tight collaboration feasible. Risk: high coordination cost.
Shared Kernel: Small shared model subset both contexts depend on. Must be small, explicitly versioned, jointly owned. Changes require agreement from both teams.
Customer-Supplier: Upstream serves downstream's needs. Downstream negotiates what upstream provides. Structured relationship with explicit API contracts.
Conformist: Downstream adopts upstream's model as-is. No negotiation. Use when: integration simplicity outweighs design freedom, or upstream won't accommodate.
Anti-Corruption Layer (ACL): Downstream creates a translation layer to isolate its model from upstream's. Essential for: legacy integration, poor upstream models, protecting domain purity.
Open Host Service (OHS): Upstream provides a well-defined API for multiple downstream consumers. Standardized protocol (REST, gRPC, GraphQL).
Published Language: Shared schema or format for inter-context communication. Examples: iCalendar, vCard, JSON Schema, Protocol Buffers.
Separate Ways: No integration. Contexts have no meaningful dependency. Duplication is acceptable when coupling cost exceeds duplication cost.
Big Ball of Mud: Recognition pattern only. Demarcate and quarantine legacy systems. Draw a boundary around them, communicate through ACL.
Do the teams need to coordinate releases?
YES -> Do both depend on each other equally?
YES -> Partnership (if feasible) or Shared Kernel (if small overlap)
NO -> Customer-Supplier (negotiate API)
NO -> Is upstream model acceptable?
YES -> Conformist (adopt as-is)
NO -> Anti-Corruption Layer (translate)
Independent? -> Separate Ways
Legacy mess? -> Big Ball of Mud + ACL
A rigorous vocabulary shared between developers and domain experts, scoped per bounded context.
Use Mermaid flowchart for context maps:
flowchart LR
subgraph Core
OrderCtx[Order Context]
CatalogCtx[Catalog Context]
end
subgraph Supporting
NotifCtx[Notification Context]
end
subgraph Generic
PaymentCtx[Payment Context]
AuthCtx[Identity Context]
end
OrderCtx -->|Customer-Supplier| CatalogCtx
OrderCtx -->|ACL| PaymentCtx
OrderCtx -->|OHS| NotifCtx
CatalogCtx -.->|Conformist| AuthCtx
Label every arrow with the context mapping pattern. Core contexts in the center.
testing
Acceptance test creation methodology for the DISTILL wave. Domain knowledge for the acceptance designer agent: port-to-port principle, prior wave reading, wave-decision reconciliation, graceful degradation, and document back-propagation.
testing
Methodology for minimizing test count while maximizing behavioral coverage - behavior definition, anti-pattern catalog, consolidation patterns, stopping criterion, coverage-preserving validation
testing
Methodology for minimizing test count while maximizing behavioral coverage - behavior definition, anti-pattern catalog, consolidation patterns, stopping criterion, coverage-preserving validation
development
Design mandates for acceptance tests - hexagonal boundary, business language abstraction, user journey completeness, pure function extraction, 3 Pillars (domain language / chained narrative / production composition), and the layered ATD discipline (Universe-bound assertion, layer-dependent PBT mode, two-tier acceptance, example-based sad paths)