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Every software program relates to some activity or interest of its user. That subject area to which the user applies the program is the domain of the software.
To create software that is valuably involved in users' activities, a development team must bring to bear a body of knowledge related to those activities. Models are tools for grappling with the volume and complexity of information. Model is a rigorously organised and selective abstraction of that knowledge.
The utility of a model in DDD.
- The model and the heart of the design shape each other.
- The model is the backbone of a language used by all team members.
- The model is distilled knowledge.
Ingredients of effective modelling.
- Binding the model and the implementation.
- Cultivating a language based on the model.
- Developing a knowledge-rich model.
- Distilling the model.
- Brainstorming and experimenting.
A project faces serious problems when its language is fractured. Domain experts use their jargon while technical team have their own language tuned for discussing the domain in terms of design.
The terminology of day-to-day discussions is disconnected from the terminology embedded in the code (ultimately the most important product of a software project). And even the same person uses different language in speech and in writing, so that the most incisive expressions of the domain often emerge in a transient form that is never captured in the code or even in writing.
Translation blunts communication and makes knowledge crunching anemic.
Yet none of these dialects can be a common language because none serves all needs.
Use the model as the backbone of a language. Commit the team to exercising that language relentlessly in all communication within the team and in the code. Use the same language in diagrams, writing, and especially speech.
Iron out difficulties by experimenting with alternative expressions, which reflect alternative models. Then refactor the code, renaming classes, methods, and modules to conform to the new model. Resolve confusion over terms in conversation, in just the way we come to agree on the meaning of ordinary words.
Recognize that a change in the UBIQUITOUS LANGUAGE is a change to the model.
Domain experts should object to terms or structures that are awkward or inadequate to convey domain understanding; developers should watch for ambiguity or inconsistency that will trip up design.
Play with the model as you talk about the system. Describe scenarios out loud using the elements and interactions of the model, combining concepts in ways allowed by the model. Find easier ways to say what you need to say, and then take those new ideas back down to the diagrams and code.
If the design, or some central part of it, does not map to the document model, that model is of little value, and the correctness of the software is suspect. At the same time, complex mappings between models and design functions are difficult to understand and, in practice, impossible to maintain as the design changes. A deadly divide opens between analysis and design so that insight gained in each of those activities does not feed into the other.
Design a portion of the software system to reflect the domain model in a very literal way, so that mapping is obvious. Revisit the model and modify it to be implemented more naturally in software, even as you seek to make it reflect deeper insight into the domain. Demand a single model that serves both purposes well, in addition to supporting a robust UBIQUITOUS LANGUAGE.
Draw from the model the terminology used in the design and the basic assignment of responsibilities. The code becomes an expression of the model, so a change to the code may be a change to the model. Its effect must ripple through the rest of the project's activities accordingly.
To tie the implementation slavishly to a model usually requires software development tools and languages that support a modelling paradigm, such as object-oriented programming.
If the people who write the code do not feel responsible for the model, or don't understand how to make the model work for an application, then the model has nothing to do with the software. If developers don't realize that changing code changes the model, then their refactoring will weaken the model rather than strengthen it. Meanwhile, when a modeler is separated from the implementation process, he or she never acquires, or quickly loses, a feel of the constraints of implementation. The basic constraint of MODEL-DRIVEN DESIGN – that the model supports an effective implementation and abstracts key domain knowledge – is half-gone, and the resulting models will be impractical. Finally, the knowledge and skills of experienced designers won't be transferred to other developers if the devision of labor prevents the kind of collaboration that conveys the subtleties of coding a MODEL-DRIVEN DESIGN.
Any technical person contributing to the model must spend some time touching the code, whatever primary role he or she plays on the project. Anyone responsible for changing code must learn to express a model through the code. Every developer must be involved in some level of discussion about the model and have contact with domain experts. Those who contribute in different ways must consciously engage those who touch the code in dynamic exchange of model ideas through the UBIQUITOUS LANGUAGE.
In an object-oriented, UI, database, and other support code often gets written directly into the business objects. Additional business logic is embedded in the behavior of UI widgets and database scripts. This happens because it is the easiest way to make things work, in the short run.
When the domain-related code is diffused through such a large amount of other code, it becomes extremely difficult to see and to reason about. Superficial changes to the UI can actually change business logic. To change a business rule may require meticulous tracing of UI code, database code, or other program elements. Implementing coherent, model-driven objects becomes impractical. Automated testing is awkward. With all the technologies and logic involved in each activity, a program must be kept very simple or it becomes impossible to understand.
- User Interface (or Presentation Layer) – Responsible for showing information to the user and interpreting the user's commands. The external actor might sometimes be another computer system rather than a human user.
- Application Layer – Defines the jobs the software is supposed to do and directs the expressive domain objects to work out problems. The tasks this layer is responsible for are meaningful to the business or necessary for interaction with the application layers or other systems. This layer is kept thin. It does not contain business rules or knowledge, but only coordinates tasks and delegates work to collaborations of domain objects in the next layer down. It does not have state reflecting the business situation, but it can have state that reflects the progress of a task for the user or the program.
- Domain Layer (or Model Layer) – Responsible for representing concepts of the business, information about the business situation, and business rules. State that reflects the business situation is controlled and used here, even though the technical details of storing it are delegated to the infrastructure. This layer is the heart of business software.
- Infrastructure Layer – Provides generic technical capabilities that support the higher layers: message sending for the application, persistence for the domain, drawing widgets for the UI, and so on. The infrastructure layer may also support the pattern of interactions between the four layers through an architectural framework.
Partition a complex program into layers. Develop a design within each layer that is cohesive and that depends only on the layers below. Follow standard architectural patters to provide loose coupling to the layers above. Concentrate all the code related to the domain model in one layer and isolate it from the user interface, application, and infrastructure code. The domain objects, free of the responsibility of displaying themselves, storing themselves, managing application tasks, and so forth, can be focused on expressing the domain model. This allows a model to evolve to be rich enough and clear enough to capture essential business knowledge and put it to work.
If an unsophisticated team with a simple project decides to try a MODEL-DRIVEN DESIGN with LAYERED ARCHITECTURE, it will face a difficult learning curve. Team members will have to master complex new technologies and stumble through the process of learning object modelling (which is challenging, even with the help of this book!). The overhead of managing infrastructure and layers makes very simple tasks take longer. Simple projects come with short time lines and modest expectations. Long before the team completes the assigned task, much less demonstrates the exciting possibilities of its approach, the project will have been cancelled.
Even if the team is given more time, the team members are likely to fail to master the techniques without expert help. And in the end, if they do surmount these challenges, they will have produced a simple system. Rich capabilities were never requested.
Put all the business logic into the user interface. Chop the application into small functions and implement them as separate user interfaces, embedding the business rules into them. Use a relation database as a shared repository of the data. Use the most automated UI building and visual programming tools available.
Some objects are not defined primarily by their attributes. They represent a thread of identity that runs through time and often across distinct representations. Sometimes such an object must be matched with another object even though attributes differ. An object must be distinguished from the other objects even though they might have the same attributes. Mistaken identity can lead to data corruption.
When an object is distinguished by its identity, rather than its attributes, make this primary to its definition in the model. Keep the class definition simple and focused on life cycle continuity and identity. Define a means of distinguishing each object regardless of its form or history. Be alert to requirements that call for matching objects by attributes. Define an operation that is guaranteed to produce a unique result for each object, possibly by attaching a symbol that is guaranteed unique. This means of identification may come from the outside, or it may be an arbitrary identifier created by and for the system, but it must correspond to the identity distinctions in the model. The model must define what it means to be the same thing.
Tracking the identity of ENTITIES is essential, but attaching identity to other objects can hurt system performance, add analytical work, and muddle the model by making all objects look the same.
Software design is a constant battle with complexity. We must make distinctions so that special handling is applied only where necessary.
However, if we think of this category of object as just the absence of identity, we haven't added much to our toolbox or vocabulary. In fact, these objects have characteristics of their own and their own significance to the model. These are the objects that describe things.
When you care only about the attributes of an element of the model, classify it as a VALUE OBJECT. Make it express the meaning of the attributes it conveys and give it related functionality. Treat the VALUE OBJECT as immutable. Don't give it any identity and avoid the design complexities necessary to maintain ENTITIES.
Some concepts from the domain aren't natural to model as objects. Forcing the required domain functionality to be the responsibility of an ENTITY or VALUE either distorts the definition of a model-based object or adds meaningless artificial objects.
When a significant process or transformation in the domain is not a natural responsibility of an ENTITY or VALUE OBJECT, add an operation to the model as a standalone interface declared as a SERVICE. Define the interface in terms of the language of the model and make sure the operation name is part of the UBIQUITOUS LANGUAGE. Make the SERVICE stateless.
Everyone uses MODULES, but few treat them as a full-fledget part of the model. Code gets broken down into all sorts of categories, from aspects of the technical architecture to developers' work assignments. Even developers who refactor a lot tend to content themselves with MODULES conceived early in the project.
It is a truism that there should be low coupling between MODULES and high cohesion within them. Explanations of coupling and cohesion tend to make them sound like technical metrics, to be judget mechanically based on the distributions of associations and interactions. Yet it isn't just code being divided into MODULES, but concepts. There is a limit to how many things a person can think about at once (hence low coupling). Incoherent fragments of ideas are as hard to understand as an undifferentiated soup of ideas (hence high cohesion).
Choose MODULES that tell the story of the system and contain a cohesive set of concepts. This often yields low coupling between MODULES, but if it doesn't, look for a way to change the model to disentangle the concepts, or search for an overlooked concept that might be the basis of a MODULE that would bring the elements together in a meaningful way. Seek low coupling in the sense of concepts that can be understood and reasoned about independently of each other. Refine the model until it partitions according to high-level domain concepts and the corresponding code is decoupled as well.
Give the MODULES names that become part of the UBIQUITOUS LANGUAGE. MODULES and their names should reflect insight into the domain.
Unless there is a real intention to distribute code on different servers, keep all the code that implements a single conceptual object in the same MODULE, if not the same object.
Use packaging to separate the domain layer from other code. Otherwise, leave as much freedom as possible to the domain developers to package the domain objects in ways that support their model and design choices.
It is difficult to guarantee the consistency of changes to objects in a model with complex associations. Invariants need to be maintained that apply to closely related groups of objects, not just discrete objects. Yet cautious locking schemes cause multiple users to interfere pointlessly with each other and make a system unusable.
Cluster the ENTITIES and VALUE OBJECTS into AGGREGATES and define boundaries around each. Choose the ENTITY to be the root of each AGGREGATE, and control all access to the objects inside the boundary through the root. Allow external objects to hold references to the root only. Transient references to internal members can be passed out for use within a single operation only. Because the root controls access, it cannot be blindsided by changes to the internals. This arrangement makes it practical to enforce all invariants for objects in the AGGREGATE and for the AGGREGATE as a whole in any state change.
Creation of an object can be a major operation in itself, but complex assembly operations do not fit the responsibility of the created objects. Combining such responsibilities can produce ungainly designs that are hard to understand. Making the client direct construction muddies the design of the client, breaches encapsulation of the assembled object of AGGREGATE, and overly couples the client to the implementation of the created object.
Shift the responsibility for creating instances of complex objects and AGGREGATES to a separate object, which may itself have no responsibility in the domain model but is still part of the domain design. Provide an interface that encapsulates all complex assembly and that does not require the client to reference the concrete classes of the objects being instantiated. Create entire AGGREGATES as a piece, enforcing their invariants.
A client needs a practical means of acquiring references to preexisting domain objects. If the infrastructure makes it easy to do so, the developers of the client may add more traversable associations, muddling the model. On the other hand, they may use queries to pull the exact data they need from the database, or to pull a few specific objects rather than navigating from AGGREGATE roots. Domain logic moves into queries and client code, and the ENTITIES and VALUE OBJECTS become mere data containers. The sheer technical complexity of applying most database access infrastructure quickly swamps the client code, which leads developers to dumb down the domain layer, which makes the model irrelevant.
A subset of persistent objects must be globally accessible through a search based on object attributes. Such access is needed for the roots of AGGREGATES that are not convenient to reach by traversal. They are usually ENTITIES, sometimes VALUE OBJECTS with complex internal structure, and sometimes enumerated VALUES. Providing access to other objects muddies important distinctions. Free database queries can actually breach the encapsulation of domain objects and AGGREGATES. Exposure of technical infrastructure and database access mechanisms complicates the client and obscures the MODEL-DRIVEN DESIGN.
For each type of object that need global access, create an object that can provide the illusion of an in-memory collection of all objects of that type. Set up access through a well-known global interface. Provide methods to add and remove objects, which will encapsulate the actual insertion or removal of data in the data store. Provide methods that select objects based on some criteria and return fully instantiated objects or collections of objects whose attribute values meet the criteria, thereby encapsulating the actual storage and query technology. Provide REPOSITORIES only for AGGREGATE roots that actually need direct access. Keep the client focused on the model, delegating all object storage and access to the REPOSITORIES.
Many transformations of domain models and the corresponding code happen when developers recognize a concept that has been hinted at in discussion or present implicitly in the design, and they then represent it explicitly in the model with one or more objects or relationships.
Listen to the language the domain experts use. Are there terms that succinctly state something complicated? Are they correcting your word choice (perhaps diplomatically)? Do the puzzled looks on their faces go away when you use a particular phrase? These are hints of a concept that might benefit the model.
Business rules often do not fit the responsibility of any of the obvious ENTITIES or VALUE OBJECTS, and their variety and combinations can overwhelm the basic meaning of the domain object. But moving the rules out of the domain layer is even worse, since the domain code no longer expresses the model.
Logic programming provides the concept of separate, combinable, rule objects called "predicates", but full implementation of this concept with objects is cumbersome. It's also so general that it doesn't communicate intent as much as more specialized designs.
Create explicit predicate-like VALUE OBJECTS for specialized purposes. A SPECIFICATION is a predicate that determines if an object does or does not satisfy some criteria.
We might need to specify the state of an object for one or more of these three purposes.
- 1.To validate an object to see if it fulfills some need or is ready for some purpose (validation).
- 2.To select an object from a collection (selection or querying).
- 3.To specify the creation of a new object to fit some need (building to order or generating).
If a developer must consider the implementation of a component in order to use it, the value of encapsulation is lost. If someone other than the original developer must infer the purpose of an object or operation based on its implementation, that new developer may infer a purpose that the operation or class fulfills only by chance. If that was not the intent, the code may work for the moment, but the conceptual basis of the design will have been corrupted, and the two developers will be working at cross-purposes.
Name classes and operations to describe their effect and purpose, without reference to the means by which they do what they promise. This relieves the client developer of the need to understand the internals. These names should conform to the UBIQUITOUS LANGUAGE so that team members can quickly infer their meaning. Write a test for a behaviour before creating it, to force your thinking into client developer mode.
Interactions of multiple rules or compositions of calculations become extremely difficult to predict. The developer calling an operation must understand its implementation and the implementation of all its delegations in order to anticipate the result. The usefulness of any abstraction of interfaces is limited if the developers are forced to pierce the veil. Without safely predictable abstractions, the developers must limit the combinatory explosion, placing a low ceiling on the richness of behaviour that is feasible to build.
Place as much of the logic of the program as possible into functions, operations that return results with no observable side effects. Strictly segregate commands (methods that result in modifications to observable state) into very simple operations that do not return domain information. Further control side effects by moving complex logic into VALUE OBJECTS when a concept fitting the responsibility presents itself.
When the side effects of operations are only defined implicitly by their implementation, designs with a lot of delegation become a tangle of cause and effect. The only way to understand a program is to trace execution through branching paths. The value of encapsulation is lost. The necessity of tracing concrete execution defeats abstraction.
State post-conditions of operations and invariants of classes and AGGREGATES. If ASSERTIONS cannot be coded directly in your programming language, write automated unit tests for them. Write them into documentation or diagrams where it fits the style of the project's development process.
Seek models with coherent sets of concepts, which lead a developer to infer the intended ASSERTIONS, accelerating the learning curve and reducing the risk of contradictory code.
When elements of a model or design are embedded in a monolithic construct, their functionality gets duplicated. The external interface doesn't say everything a client might care about. Their meaning is hard to understand, because different concepts are mixed together.
On the other hand, breaking down classes and methods can pointlessly complicate the client, forcing client objects to understand how tiny pieces fit together. Worse, a concept can be lost completely. Half of a uranium atom is not uranium. And of course, it isn't just grain size that counts, but just where the grain runs.
Decompose design elements (operations, interfaces, classes, and AGGREGATES) into cohesive units, taking into consideration your intuition of the important divisions in the domain. Observe the axes of change and stability through successive refactorings and look for the underlying CONCEPTUAL CONTOURS that explain these shearing patterns. Align the model with the consistent aspects of the domain that make it a viable area of knowledge in the first place.
Even within a MODULE, the difficulty of interpreting a design increases wildly as dependencies are added. This adds to mental overload, limiting the design complexity a developer can handle. Implicit concepts contribute to this load even more than explicit references.
Low coupling is fundamental to object design. When you can, go all the way. Eliminate all other concepts from the picture. Then the class will be completely self-contained and can be studied and understood alone. Every such self-contained class significantly eases the burden of understanding a MODULE.
Most interesting objects end up doing things that can't be characterized by primitives alone.
Where it fits, define an operation whose return type is the same as the type of its argument(s). If the implementer has state that is used in the computation, then the implementer is effectively an argument of the operation, so the argument(s) and return value should be of the same type as the implementer. Such an operation is closed under the set of instances of that type. A closed operation provides a high-level interface without introducing any dependency on other concepts.
Domain models contain processes that are not technically motivated but actually meaningful in the problem domain. When alternative processes must be provided, the complexity of choosing the appropriate process combines with the complexity of the multiple processes themselves, and things get out of hand.
Factor the varying part of a process into a separate "strategy" object in the model. Factor apart a rule and the behavior it governs. Implement the rule or substitutable process following the STRATEGY design pattern. Multiple versions of the strategy object represent different ways the process can be done.
When the relatedness of nested containers is not reflected in the model, common behavoir has to be duplicated at each level of the hierarchy, and nesting is rigid (for example, containers can't usually contain other containers at their own level, and the number of levels is fixed). Clients must deal with different levels of the hierarchy through different interfaces, even though there may be no conceptual difference they care about. Recursion through the hierarchy to produce aggregated information is very complicated.
Define an abstract type that encompasses all members of the COMPOSITE. Methods that return information are implemented on containers to return aggregated information about their contents. "Leaf" nodes implement those methods based on their own values. Clients deal with the abstract type and have no need to distinguish leaves from containers.
Total unification of the domain model for a large system will not be feasible or cost-effective.
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 confused. It is often unclear in what context a model should not be applied.
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.
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.
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.
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.
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. Take up transformations later.
Uncoordinated teams working on closely related applications can go racing forward for a while, but what they produce may not fit together. They can end up spending more on translation layers and retrofitting than they would have on CONTINUOUS INTEGRATION in the first place, meanwhile duplicating effort and losing the benefits of a common UBIQUITOUS LANGUAGE.
Designate some subset of the domain model that the two teams agree to share. Of course this includes, along with this subset of the model, the subset of code or of the database design associated with that part of the model. This explicitly shared stuff has special status, and shouldn't be changed without consultation with the other team.
Integrate a functional system frequently, but somewhat less often then the pace of CONTINUOUS INTEGRATION within the teams. At these integrations, run the tests of both teams.
The freewheeling development of the upstream team can be cramped if the downstream team has veto power over changes, or if procedures for requesting changes are too cumbersome. The upstream team may even be inhibited, worried about breaking the downstream system. Meanwhile, the downstream team can be helpless, at the mercy of upstream priorities.
Establish a clear customer/supplier relationship between the two teams. In planning sessions, make the downstream team play the customer role to the upstream team. Negotiate and budget tasks for downstream requirements so that everyone understands the commitment and schedule.
Jointly develop automated acceptance tests that will validate the interface expected. Add these tests to the upstream team's test suite, to be run as part of its continuous integration. This testing will free the upstream team to make changes without fear of side effects downstream.
When two development teams have an upstream/downstream relationship in which the upstream has no motivation to provide for the downstream team's needs, the downstream team is helpless. Altruism may motivate upstream developers to make promises, but they are unlikely to be fullfilled. Belief in those good intentions leads the downstream team to make plans based on features that will never be available. The downstream project will be delayed until the team ultimately learns to live with what it is given. An interface tailored to the needs of the downstream team is not in the cards.
Eliminate the complexity of translation between BOUNDED CONTEXTS by slavishly adhering to the model of the upstream team. Although this cramps the style of the downstream designers and probably does not yield the ideal model for the application, choosing CONFORMITY enormously simplifies integration. Also, you will share a UBIQUITOUS LANGUAGE with your supplier team. The supplier is in the driver's seat, so it is good to make communication easy for them. Altruism may be sufficient to get them to share information with you.
When a new system is being build that must have a large interface with another, the difficulty of relating the two models can eventually overwhelm the intent of the new model altogether, causing it to be modified to resemble the other system's model, in an ad hoc fashion. The models of legacy systems are usually weak, and even the exception that is well developed may not fit the needs of the current project. Yet there may be a lot of value in the integration, and sometimes it is an absolute requirement.
Create an isolating layer to provide clients with functionality in terms of their own domain model. The layer talks to the other system through its existing interface, requiring little or no modification to the other system. Internally, the layer translates in both directions as necessary between the two models.
Integration is always expensive. Sometimes the benefit is small.
Declare a BOUNDED CONTEXT to have no connection to the others at all, allowing developers to find simple, specialized solutions within this small scope.
When a subsystem has to be integrated with many others, customizing a translator for each can bog down the team. There is more and more to maintain, and more and more to worry about when changes are made.
Define a protocol that gives access to your subsystem as a set of SERVICES. Open the protocol so that all who need to integrate with you can use it. Enhance and expand the protocol to handle new integration requirements, except when a single team has idiosyncratic needs. Then, use a one-off translator to augment the protocol for that special case so that the shared protocol can stay simple and coherent.
Direct translation to and from the existing domain models may not be a good solution. Those models may be overly complex or poorly factored. They are probably undocumented. If one is used as a data interchange language, it essentially becomes frozen and cannot respond to new development needs.
Use a well-documented shared language that can express the necessary domain information as a common medium of communication, translating as necessary into and out of that language.
In designing a large system, there are so many contributing components, all complicated and all absolutely necessary to success, that the essence of the domain model, the real business asset, can be obscured and neglected.
The harsh reality is that not all parts of the design are going to be equally refined. Priorities must be set. To make the domain model an asset, the model's critical core has to be sleek and fully leveraged to create application functionality. But scarce, highly skilled developers tend to gravitate to technical infrastructure or neatly definable domain problems that can be understood without specialized domain knowledge.
Boil the model down. Find the CORE DOMAIN and provide a means of easily distinguishing it from the mass of supporting model and code. Bring the most valuable and specialized concepts into sharp relief. Make the CORE small.
Apply top talent to the CORE DOMAIN, and recruit accordingly. Spend the effort in the CORE to find a deep model and develop a supple design – sufficient to fullfill the vision of the system. Justify investment in any other part by how it supports the distilled CORE.
Some parts of the model add complexity without capturing or communicating specialized knowledge. Anything extraneous makes the CORE DOMAIN harder to discern and understand. The model clogs up with general principles everyone knows or details that belong to specialties which are not your primary focus but play a supporting role. Yet, however generic, these other elements are essential to the functioning of the system and the full expression of the model.
Identify cohesive subdomains that are not the motivation for your project. Factor out generic models of these subdomains and place them in separate MODULES. Leave no trace of your specialties in them.
Once they have been separated, give their continuing development lower priority than the CORE DOMAIN, and avoid assigning your core developers to the tasks (because they will gain little domain knowledge from them). Also consider off-the-shelf solutions or published models for these GENERIC SUBDOMAINS.
At the beginning of a project, the model usually doesn't even exist, yet the need to focus its development is already there. In later stages of development, there is a need for an explanation of the value of the system that does not require an in-depth study of the model. Also, the critical aspects of the domain model may span multiple BOUNDED CONTEXTS, but by definition these distinct models can't be structured to show their common focus.
Write a short description (about one page) of the CORE DOMAIN and the value it will bring, the "value proposition". Ignore those aspects that do not distinguish this domain model from others. Show how the domain model serves and balances diverse interests. Keep it narrow. Write this statement early and revise it as you gain new insight.
Even though team members may know broadly what constitutes the CORE DOMAIN, different people won't pick out quite the same elements, and even the same person won't be consistent from one day to the next. The mental labor of constantly filtering the model to identify the key parts absorbs concentration better spent on design thinking, and it requires comprehensive knowledge of the model. The CORE DOMAIN must be made easier to see.
Significant structural changes to the code are the ideal way of identifying the CORE DOMAIN, but they are not always practical in the short term. In fact, such major code changes are difficult to undertake without the very view the team is lacking.
- The Distillation Document – Write a very brief document (three to seven sparse pages) that describes the CORE DOMAIN and the primary interactions among core elements.
- The Flagged Core – Flag each element of the CORE DOMAIN within the primary repository of the model, without particularly trying to elucidate its role. Make it effortless for a developer to know what is in or out of the CORE.
- The Distillation Document as Process Tool – If the distillation document outlines the essentials of the CORE DOMAIN, then it serves as a practical indicator of the significance of a model change. When a model or code change affects the distillation document, it requires consultation with other team members. When the change is made, it requires immediate notification of all team members, and the dissemination of a new version of the document. Changes outside the CORE or to details not included in the distillation document can be integrated without consultation or notification and will be encountered by other members in the course of their work. Then the developers have the full autonomy that XP suggests.
Computations sometimes reach a level of complexity that begins to bloat the design. The conceptual "what" is swamped by the mechanistic "how". A large number of methods that provide algorithms for resolving the problem obscure the methods that express the problem.
Partition a conceptually COHESION MECHANISM into a separate lightweight framework. Particularly watch for formalisms or well-documented categories of algorithms. Expose the capabilities of the framework with an INTENTION-REVEALING INTERFACE. Now the other elements of the domain can focus on expressing the problem ("what"), delegating the intricacies of the solution ("how") to the framework.
Elements in the model may partially serve the CORE DOMAIN and partially play supporting roles. CORE elements may be tightly coupled to generic ones. The conceptual cohesion of the CORE may not be strong or visible. All this clutter and entanglement chokes the CORE. Designers can't clearly see the most important relationships, leading to a weak design.
Refactor the model to separate the CORE concepts from supporting players (including ill-defined ones) and strengthen the cohesion of the CORE while reducing its coupling to other code. Factor all generic or supporting elements into other objects and place them into other packages, even if this means refactoring the model in ways that separate highly coupled elements.
When there is a lot of interaction between subdomains in separate MODULES, either many references will have to be created between MODULES, which defeats much of the value of the partitioning, or the interaction will have to be made indirect, which makes the model obscure.
Identify the most fundamental concepts in the model and factor them into distinct classes, abstract classes, or interfaces. Design this abstract model so that it expresses most of the interaction between significant components. Place this abstract overall model in its own MODULE, while the specialized, detailed implementation classes are left in their own MODULES defined by subdomain.
Although a breakthrough to a deep model provides value anywhere it happens, it is in the CORE DOMAIN that it can change the trajectory of an entire project.
In a large system without any overarching principle that allows elements to be interpreted in terms of their role in patterns that span the whole design, developers cannot see the forest for the trees.
Devise a pattern of rules or roles and relationships that will span the entire system and that allows some understanding of each part's place in the whole – even without detailed knowledge of the part's responsibility.
Design free-for-all produces systems no one can make sense of as a whole, and they are very difficult to maintain. But architectures can straitjacket a project with up-front design assumptions and take too much power away from the developers/designers of particular parts of the application. Soon, developers will dumb down the application to fit the structure, or they will subvert it and have no structure at all, bringing back the problems of uncoordinated development.
Let this conceptual large-scale structure evolve with the application, possibly changing to a completely different type of structure along the way. Don't overconstrain the detailed design and model decisions that must be made with detailed knowledge.
Large-scale structure should be applied when a structure can be found that greatly clarifies the system without forcing unnatural constraints on model development. Because an ill-fitting structure is worse than none, it is best not to shoot for comprehensiveness, but rather to find a minimal set that solves the problems that have emerged. Less is more.
Software designs tend to be very abstract and hard to grasp. Developers and users alike need tangible ways to understand the system and share a view of the system as a whole.
When a concrete analogy to the system emerges that captures the imagination of team members and seems to lead thinking in a useful direction, adopt it as a large-scale structure. Organize the design around this metaphor and absorb it into the UBIQUITOUS LANGUAGE. The SYSTEM METAPHOR should both facilitate communication about the system and guide development of it. This increases consistency in different parts of the system, potentially even across different BOUNDED CONTEXTS. But because all metaphors are inexact, continually reexamine the metaphor for overextension or inaptness, and be ready to drop it if it gets in the way.
When each individual object has handcrafted responsibilities, there are no guidelines, no uniformity, and no ability to handle large swaths of the domain together. To give coherence to a large model, it is useful to impose some structure on the assignment of those responsibilities.
Look at the conceptual dependencies in your model and the varying rates and sources of change of different parts of your domain. If you identify natural strata in the domain, cast them as broad abstract responsibilities. These responsibilities should tell a story of the high-level purpose and design of your system. Refactor the model so that the responsibilities of each domain object, AGGREGATE, and MODULE fit neatly within the responsibility of one layer.
In an application in which the roles and relationships between ENTITIES vary in different situations, complexity can explode. Neither fully general models nor highly customized ones serve the user's needs. Objects end up with references to other types to cover a variety of cases, or with attributes that are used in different ways in different situations. Classes that have the same data and behavior may multiply just to accommodate different assembly rules.
Create a distinct set of objects that can be used to describe and constrain the structure and behavior of the basic model. Keep these concerns separate as two "levels", one very concrete, the other reflecting rules and knowledge that a user or superuser is able to customize.
When a variety of applications have to interoperate, all based on the same abstractions but designed independently, translations between multiple BOUNDED CONTEXTS limit integration. A SHARED KERNEL is not feasible for teams that do not work closely together. Duplication and fragmentation raise costs for development and installation, and interoperability becomes very difficult.
Distill an ABSTRACT CORE of interfaces and interactions and create a framework that allows diverse implementations of those interfaces to be freely substituted. Likewise, allow any application to use those components, so long as it operates strictly through the interfaces of the ABSTRACT CORE.