Pc Domain Modeling

Domain Modeling

Model the business language before modeling storage, APIs, or implementation.

Context

Domain modeling turns reviewed requirements into a stable business-language contract.

See context and anti-pattern notes.

Inputs

I/O contract notes define required inputs and authority.

Process

Step 1: Identify Core Entities

Extract the nouns and verb phrases that represent real business concepts:

• campaign
• reviewer assignment
• evidence package
• policy exception

Prefer concepts from the problem space, not solution-space placeholders like table, queue, endpoint, or job.

Step 2: Define Relationships

Map how entities relate and where the relationship is authoritative:

• one-to-one / one-to-many / many-to-many
• optional vs required
• source-of-truth vs derived view
• transitional or compatibility-only relationship when brownfield coexistence is in play

Step 3: Establish Ubiquitous Language

Create a glossary of domain terms with precise definitions. Resolve synonyms:

• Is "Customer" the same as "User"? If not, what's the difference?
• Is an "Order" created when the user clicks "Buy" or when payment succeeds?

Record legacy or tenant-specific terms separately when they must remain visible but should not silently dominate the new model.

Step 4: Identify Bounded Contexts

Introduce bounded contexts only when the requirements justify a real language or responsibility split:

• Order Context: Order, LineItem, Discount
• Payment Context: Payment, Refund, Invoice
• User Context: Account, Profile, Preferences

Do not force DDD vocabulary onto a simple slice that only needs one coherent domain model.

Step 5: Validate with Domain Experts

Walk the model against real scenarios from the requirements:

• happy path
• error or exception path
• brownfield or compatibility boundary

The model should make those scenarios easier to explain without leaking into schema or endpoint design.

Outputs

Produce only declared outputs at their documented quality boundary.

Quality Gate

• Core entities and relationships documented visually (ER diagram or similar)
• Ubiquitous language glossary created with team agreement
• Bounded contexts identified (if system is complex enough to warrant them)
• Model validated against at least 3 real business scenarios