Domain-driven design (DDD) is the concept that the structure and language of software code (class names, class methods, class variables) should match the business domain. For example, if a software processes loan applications, it might have classes such as LoanApplication and Customer, and methods such as AcceptOffer and Withdraw.

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DDD connects the implementation to an evolving model.^[1]

Domain-driven design is predicated on the following goals:

placing the project's primary focus on the core domain and domain logic;
basing complex designs on a model of the domain;
initiating a creative collaboration between technical and domain experts to iteratively refine a conceptual model that addresses particular domain problems.

The term was coined by Eric Evans in his book of the same title.^[2]

Concepts[edit]

Concepts of the model include:

Context: The setting in which a word or statement appears that determines its meaning;
Domain: A sphere of knowledge (ontology), influence, or activity. The subject area to which the user applies a program is the domain of the software;
Model: A system of abstractions that describes selected aspects of a domain and can be used to solve problems related to that domain;
Ubiquitous Language: A language structured around the domain model and used by all team members to connect all the activities of the team with the software.

Strategic domain-driven design[edit]

Semantic network of patterns in strategic domain-driven design.

Ideally, it would be preferable to have a single, unified model.^{[citation needed]} While this is a noble goal, in reality it typically fragments into multiple models. It is useful to recognize this fact of life and work with it.

Strategic Design is a set of principles for maintaining model integrity, distilling the Domain Model, and working with multiple models.^{[citation needed]}

Bounded context[edit]

Multiple models are in play on any large project. Yet when code based on distinct models is combined, software becomes buggy, unreliable, and difficult to understand. Communication among team members becomes confusing. It is often unclear in what context a model should not be applied.

Therefore:Explicitly define the context within which a model applies. Explicitly set boundaries in terms of team organization, usage within specific parts of the application, and physical manifestations such as code bases and database schemas. Keep the model strictly consistent within these bounds, but don't be distracted or confused by issues outside and inside.

Continuous integration[edit]

When a number of people are working in the same bounded context, there is a strong tendency for the model to fragment. The bigger the team, the bigger the problem, but as few as three or four people can encounter serious problems. Yet breaking down the system into ever-smaller contexts eventually loses a valuable level of integration and coherency.

Therefore:Institute a process of merging all code and other implementation artifacts frequently, with automated tests to flag fragmentation quickly. Relentlessly exercise the ubiquitous language to hammer out a shared view of the model as the concepts evolve in different people's heads.

Context map[edit]

An individual bounded context leaves some problems in the absence of a global view. The context of other models may still be vague and in flux.

People on other teams won't be very aware of the context bounds and will unknowingly make changes that blur the edges or complicate the interconnections. When connections must be made between different contexts, they tend to bleed into each other.

Therefore:Identify each model in play on the project and define its bounded context. This includes the implicit models of non-object-oriented subsystems. Name each bounded context, and make the names part of the ubiquitous language.Describe the points of contact between the models, outlining explicit translation for any communication and highlighting any sharing. Map the existing terrain.

Building blocks[edit]

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In the book Domain-Driven Design,^[2] a number of high-level concepts and practices are articulated, such as ubiquitous language meaning that the domain model should form a common language given by domain experts for describing system requirements, that works equally well for the business users or sponsors and for the software developers. The book is very focused on describing the domain layer as one of the common layers in an object-oriented system with a multilayered architecture. In DDD, there are artifacts to express, create, and retrieve domain models:

Entity: An object that is not defined by its attributes, but rather by a thread of continuity and its identity.; Example: Most airlines distinguish each seat uniquely on every flight. Each seat is an entity in this context. However, Southwest Airlines, EasyJet and Ryanair do not distinguish between every seat; all seats are the same. In this context, a seat is actually a value object.
Value object: An object that contains attributes but has no conceptual identity. They should be treated as immutable.; Example: When people exchange business cards, they generally do not distinguish between each unique card; they are only concerned about the information printed on the card. In this context, business cards are value objects.
Aggregate: A collection of objects that are bound together by a root entity, otherwise known as an aggregate root. The aggregate root guarantees the consistency of changes being made within the aggregate by forbidding external objects from holding references to its members.; Example: When you drive a car, you do not have to worry about moving the wheels forward, making the engine combust with spark and fuel, etc.; you are simply driving the car. In this context, the car is an aggregate of several other objects and serves as the aggregate root to all of the other systems.
Domain Event: A domain object that defines an event (something that happens). A domain event is an event that domain experts care about.
Service: When an operation does not conceptually belong to any object. Following the natural contours of the problem, you can implement these operations in services. See also Service (systems architecture).
Repository: Methods for retrieving domain objects should delegate to a specialized Repository object such that alternative storage implementations may be easily interchanged.
Factory: Methods for creating domain objects should delegate to a specialized Factory object such that alternative implementations may be easily interchanged.

Disadvantages[edit]

In order to help maintain the model as a pure and helpful language construct, the team must typically implement a great deal of isolation and encapsulation within the domain model. Consequently, a system based on domain-driven design can come at a relatively high cost. While domain-driven design provides many technical benefits, such as maintainability, Microsoft recommends that it be applied only to complex domains where the model and the linguistic processes provide clear benefits in the communication of complex information, and in the formulation of a common understanding of the domain.^[3]

Relationship to other ideas[edit]

Object-orient