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Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. Viniflora ® FrootZen™ First direct inoculation yeast for winemakers… First Pichia kluyveri yeast product… First… for New Zealand winemakers! In this week's podcast QCon chair Wesley Reisz talks to Matt Ranney who is the Chief Systems Architect at Uber, where he's helping build and scale everything he can.
David Talby demos using Python libraries to build a ML model for fraud detection, scaling it up to billions of events using Spark, and what it took to make the system perform and ready for production. Domain Driven Design (DDD) is about mapping business domain concepts into software artifacts.
The objective of this article is to cover the domain modeling and design from a practical stand-point on how one would go about taking a domain model and actually implementing it. This article talks about how these different factors affect the implementation project throughout its lifecycle and what the architects should look for in realizing a successful DDD implementation.
AppDynamics is an application intelligence company solution that simplifies the management of complex, business-critical apps.
The article includes a sample loan processing application to demonstrate how design aspects and development best practices discussed here, can be used in a real-world domain driven development project. It helps the team create a common model, between the business and IT stakeholders in the company, that the team can use to communicate about the business requirements, data entities, and process models.
The model is modular, extensible and easy to maintain as the design reflects the business model.
On the flip side, let's see what happens when IT teams don't follow a domain model approach for developing medium to large size enterprise software applications. Anemic domain models, in most cases, are not cost-effective; they don't give the company a competitive advantage over other companies because implementing business requirement changes in this architecture take too long to develop and deploy to production environment. Before we look at different architectural and design considerations in a DDD implementation project, let's take a look at the characteristics of a rich domain model. It should be isolated from other domains in the business as well as other layers in the application architecture. It should be reusable to avoid any duplicate models and implementations of the same core business domain elements.
The model should be designed loosely coupled with other layers in the application, meaning no dependencies on the layers on either side of domain layer (i.e.
It should be an abstract and cleanly separated layer enabling easier maintenance, testing, and versioning. It should be designed using a POJO programming model without any technology or framework dependencies (I always tell the project teams I work with in my company, that the technology we use for software development is Java). The domain model should be independent of persistence implementation details (although the technology does place some constraints on the model). It should have minimum dependencies on any infrastructure frameworks because it will outlive these frameworks and we don't want any tight coupling on any external framework. In order to achieve a better Return On Investment (ROI) on software development efforts, the senior management in Business Units and IT has to commit to the investment (of time, money, and resources) in business domain modeling and its implementation. IT team (modelers, architects, and developers) should possess good modeling and design skills. Architects and developers should have strong Object Oriented Design (OOD) and Programming (OOP) experience. Service Oriented Architecture (SOA) is gaining more and more momentum in the recent past to help the teams build software components and services based on the business processes and to speed up the time to market for the new products. An SOA effort should include the design and implementation of the domain model if one doesn't already exist.
An ideal scenario is the one where DDD effort is implemented iteratively with developing the application layer and SOA components at the same time as these are the direct consumers of domain model elements. Select a candidate business process and work with the business domain experts to document it using the Ubiquitous Language. Identify and document the state and behavior of the objects used by services identified in the previous step. It's important to keep the model at a high-level initially focusing on the core elements of the business domain. From a project management stand-point, a real-world DDD implementation project comprises the same phases as any other software development project. Refine and refactor the domain model based on the design and development (Continuous Integration (CI) of model concepts). An agile software development methodology is a great fit here because agile methodologies focus on the delivery of business value just like DDD focuses on the alignment of software system with business model. Start without a service layer initially and only add services where the logic doesn't belong in any domain entity or value object. Use Ubiquitous Language, Design by Contract (DbC), Automated Tests, CI and Refactoring to make the implementation as closely aligned as possible with the domain model. From the design and implementation stand-point, a typical DDD framework should support the following features. It should support the design and implementation of a business domain model using the DDD concepts. It should support concepts like Dependency Injection (DI) and Aspect Oriented Programming (AOP) out of the box. The sample application used in this article is a home loan processing system and the business use case is to approve the funding request of a home loan (mortgage). Funding module in the loan processing system automates the process of disbursement of funds to the borrower. User Interface (Presentation Layer): Responsible for presenting information to the user and interpreting user commands.
Figure 2 below shows the different architecture layers used in the application and how they relate to DDD. In a typical Unit of Work (UOW), domain objects need to collaborate with other objects whether they are Services, Repositories or Factories. When it comes to managing the code dependencies without tight-coupling between objects and isolating cross-cutting concerns, OOP alone cannot provide an elegant design solution for domain driven design and development. Loan processing application uses custom Aspects to introduce data caching into the Service objects.
Chris Richardson also discussed about using DI, objects, and Aspects to improve the application design by reducing coupling and increasing modularity. We should take advantage of annotations to generate the boiler plate code where it adds value in terms of flexibility. Application security in the domain layer ensures only authorized clients (human users or other applications) are calling the domain operations as well as accessing the domain state.
Spring Security (a sub-project in Spring Portfolio) provides a fine-grained access control in both presentation (URL based) and domain (Method Level) layers of the application. The main advantage of using Spring Security for managing the authorization requirements in the domain model is that the framework has a non-invasive architecture so we can have a clean separation between the domain and security aspects. In domain and service classes, authorization is managed at the class method invocation level.
The following table is a summary of various application security concerns in each layer of the application architecture.
Also, if we are not diligent in the application, design business rules will end up being coded in the form of several switch statements in the code. Validation rules are usually implemented in different languages like Javascript, XML, Java code, and other scripting languages. It's important to keep in mind the unit testing aspect when writing the domain classes to manage business rules. The sample application includes a business rule set to validate the loan parameters are within the allowed product and rate specifications. From a design stand-point, the domain layer should have a well defined boundary to avoid the corruption of the layer from non-core domain layer concerns such as vendor-specific translations, data filtering, transformations, etc. Entities, Value Objects, and Aggregates which contain both state (data) and behavior (operations), should have clearly defined state and behavior. In most of the use cases, we don't really have to be able to change the state of an object directly. Repository: The Repository contains domain-centric methods and uses the DAO to interact with the database. On the flip side of the best practices and design patterns, there are some DDD smells that architects and developers should watch out for when implementing the domain model.
Fat Service Layer: This is where service classes will end up having all the business logic.
Feature Envy: This is one of the classic smells mentioned in Martin Fowler's book on Refactoring where the methods in a class are far too interested in data belonging to other classes. Repositories speak the Ubiquitous Language of the domain, work with all necessary DAOs and provide data access services to the domain model in a language the domain understands. DAO methods are fine-grained and closer to the database while the Repository methods are more coarse-grained and closer to the domain. Managing the dependencies between domain objects (for example, the dependency between an Entity and its Repository) is a classic problem that developers often run into. Sample application follows these design principles in implementing the loan processing domain model. With grid computing products such as Oracle Coherence, WebSphere Object Grid, and GigaSpaces that offer data grid solutions, the developers don't even need to think about a RDBMS when they model and design the business domain. When we talk about the state (data) of the domain layer, we have to talk about the aspect of caching.


Loan processing sample application uses JBossCache framework to cache product and rate details to minimize the database calls and improve application performance.
Transaction management is important to keep the data integrity and to commit or rollback the UOW as a whole. Some developers prefer managing the transactions in the DAO classes which is a poor design. FundingServiceImpl class in the sample application manages transactions for the funding request and executes multiple database operations by calling the Repositories and commits or rolls back all database changes in a single transactions.
DTO's are also an important part of the design in an SOA environment where the Domain object model structurally is not compatible with the messages that are received and sent from a business service.
From a DDD perspective, DTO's also help maintain the separation between Service and UI layers where DO's are used in the domain and service layers and DTO's are used in the presentation layer.
Frameworks like Spring and Real Object Oriented (ROO), Hibernate, and Dozer aid in designing and implementing a domain model. Spring takes care of instantiating and wiring together the domain classes such as Services, Factories, and Repositories. Client calls a Facade class sending data as an XML document (which is XSD compliant); Facade class initiates a new transaction for the UOW.
Make any separation of attributes (like splitting a customer name into first and last name attributes in a Customer Entity object). Make any merge or separation of data elements (such as combining first and last names into single customer name attribute). The following table shows different objects that carry the data from one layer to another in the application. As you can see there are few layers in the application architecture where same data flows through in different forms (DO, DTO, XML, etc).
Frameworks like ROO also create a standard and consistent project template (using Maven plugin) for new projects.
It could be overwhelming when we consider the myriad of classes and configuration files needed to develop a typical enterprise software application.
For the test classes generated, a good option is to create abstract methods for the methods with complex business logic in the main class that need to be unit tested. Scripting languages are a better choice for writing code generators as they have less overhead and they support template creation and customization options. Table 4 below lists different layers in a web application architecture and what artifacts (Java classes or XML files) can be generated in that layer. Refactoring is changing or restructuring the application code without changing the functionality or behavior of the application. Refactoring plays an important role in the DDD project due to its iterative and evolutionary nature of domain modeling. Previously, Matt was a founder and CTO of Voxer, probably the largest and busiest deployment of Node.js. Michael Nir speaker and Agile coach shares the expert best practices; Too much Scrum might lead us to the dark side of the force. We will look at the guidelines, best practices, frameworks and tools that the technical leads and architects can use in the implementation effort.
I will start off with a list of characteristics a typical domain model should have, and when to use a domain model in an enterprise (versus not using a domain model at all or using an anemic domain model). The sample application uses frameworks like Spring, Dozer, Spring Security, JAXB, Arid POJOs and Spring Dynamic Modules in implementing the loan processing domain model. This approach also leads to domain specific business logic and rules being scattered (and duplicated in some cases) in several different facade classes. The domain classes should be unit testable outside the container (and from inside the IDE). Since one of the goals of EA is to align IT with the business units, the domain model which is the representation of business entities, becomes a core part of EA.
Domain driven design is a key element of SOA architecture because it helps in encapsulating the business logic and rules in domain objects. If we put too much emphasis on the SOA services and ignore the importance of domain model, we will end up with an anemic domain model and bloated services in the application architecture. With a rich domain implementation, SOA design will become relatively simple by providing a shell (proxy) to the domain objects. These services can be atomic (single step) or orchestrated (multi-step with or without work-flow) in nature. Also, with the iterative nature of DDD, agile methodologies such as SCRUM or DSDM are better frameworks to manage the project. Ramnivas Laddad recommends the following steps on how to go about implementing a domain object model.
When a loan application is submitted to a mortgage lending company, it first goes through the Underwriting process where the underwriters approve or deny the loan request based on customer's income details, credit history and other factors. The funding process typically starts with mortgage lender (typically a bank) forwarding the loan package to a title company. It provides communication between layers, implements persistence for business objects, contains supporting libraries for the user interface layer, etc.
Services encapsulate behavior of the business domain that doesn't fit in the domain objects themselves.
Domain objects should be designed using Plain Java Classes and Interfaces by taking advantage of OOP concepts like inheritance, encapsulation, and polymorphism. Domain objects also need to manage other concerns such as domain state change tracking, auditing, caching, transaction management (including transaction retry) which are cross-cutting in nature. This is where design concepts like DI and AOP can be used to complement OOP to minimize tight coupling, enhance modularity and better manage the cross-cutting concerns.
Loan product and interest rate information is loaded from the database table once (the first this information is requested by the client) and is then stored in an object cache (JBossCache) for subsequent product and rate lookups. The discussion was based on a presentation by Ramnivas Laddad where he made the assertion that DDD cannot be implemented without help of AOP and DI. Annotations help in minimizing the required artifacts for implementing the remote services such as EJB or Web Services.
The framework uses Spring's Bean Proxy to intercept method invocation and apply security constraints. They define data validation and other constraints that need to be applied on domain objects in specific business process scenarios. Context specificity dictates the domain object collaboration as well as other run-time factors like what business rules to apply etc. This may be an acceptable solution in small size applications, but it is not recommended for mid-size to large enterprise applications that contain complex business rules. But due to the dynamic nature of business rules, scripting languages such as Ruby, Groovy, or Domain Specific Languages (DSL) are a better choice to define and manage these rules. The rules are defined in a scripting language (Groovy) and are applied on the loan data passed to FundingService object.
At the same time, this behavior should not extend beyond the limits of the object's boundaries. When designing the domain objects, only provide setter methods for those fields that can change. So, instead of changing the internal state, create a new object with the changed state and return the new object.
They can be used for encapsulating complex, intrusive, and state-dependent requirements in the domain classes. Bitemporal framework, which is based on Martin Fowler's Temporal Patterns, provides a design approach to dealing with bitemporal issues in the domain models. As a result of these anti-patterns, domain layer becomes the least important part in application architecture and facade classes assume a more important role in the model. This is the reason why injecting the Repository instead of a DAO results in a much cleaner domain model. The usual design solution to this problem is to have the Service or Facade class call a Repository directly and when invoked the Repository would return the Entity object to the client. JPA provides this abstraction by hiding the details of the persistence implementation from the classes. Frequently accessed domain data (such as products and rates in a mortgage loan processing application) are good candidates for caching. There has always been a debate about where the transactions should be managed in the application architecture layers.
This results in too fine-grained transaction control which doesn't give the flexibility of managing the use cases where the transactions span multiple domain objects. The messages are typically defined and maintained in as XML Schema Definition documents (XSD's) and it's a common practice to write (or code generate) DTO objects from the XSD's and use them for data (message) transfer purposes between domain and SOA service layers.
It is bi-directional which saves a lot of extra code and time when converting domain objects into DTO's and vice-versa. The mapping also takes care of the aggregation of the funding response data from the Entities into a single DTO object on the way back to the client. Other frameworks that support DDD implementation are JMatter, Naked Objects, Ruby On Rails, Grails, and Spring Modules XT Framework. The framework was developed to reduce the boiler-plate coding of the patterns found in web application development.
For example, it distinguishes the state managed fields, the persistence layer uses field-level access, and the public constructors only reflect the mandatory fields.
The implementation phase should include automating the development tasks as much as possible.


Most of these objects (Java or XML) that hold data as well as other classes like DAO, DAOImpl, and DAOTest are infrastructural in nature. Using a pre-generated project template, we can achieve consistency in the directory structure on where to store the source and test classes, configuration files, and dependencies on internal and external (third-party) component libraries. Since most of these classes are basically facades to domain classes they are good candidates for code generation. This way, developers can extend the generated base test class and implement custom business logic which cannot be auto-generated. If we take advantage of code generation in a DDD project, we only need to write a few classes from scratch. One way to integrate refactoring tasks into the project is to add it in each iteration of the project before calling the iteration done. Use the combination of refactoring, CI, and unit testing to make sure the code changes didn't break any functionality and at the same time the changes did help with the intended code or performance improvements. These writings discuss the main elements of DDD such as Entity, Value Object, Service etc or they talk about concepts like Ubiquitous Language, Bounded Context and Anti-Corruption Layer.
The example code will be in Java, but it should be fairly easy to understand for most developers, regardless of language background.
This is why most of the EA components (business or infrastructural) should be designed and implemented around the domain model. The domain model also provides the language and context with which the service contract can be defined. But if we focus too much on the SOA layer without a decent domain model in the back-end, the business services will be calling an incomplete domain model, which can result in a brittle SOA architecture.
Using SCRUM (for project management) and XP (for software development purposes) methodologies is a good combination for managing a DDD implementation project. If the loan application is approved by underwriting group, it goes through Closing and Funding steps in the loan approval process. The title company then reviews the loan package and schedules a date with seller and buyer of the property for closing the loan. It does not hold the state of business objects, but it can hold the state of an application task's progress. Persistence of the business objects and possibly their state is delegated to the infrastructure layer.
Examples of business entities in a loan processing application are Mortgage, Property, and Borrower. Most of the domain elements are true objects with both State (attributes) and Behavior (methods or operations that act on the state).
These are reusable non-domain related concerns that typically tend to be scattered and duplicated all over the code including the domain layer. DI facilitates a cleaner and loosely coupled design by injecting the other objects such as Repositories and Services into Domain Objects. Similarly, other Java EE resources like DataSource, Hibernate Session Factory and Transaction Manager are injected into Service and Repository objects.
It can be used to inject collaborating objects and services into domain objects especially the objects that are not instantiated by the container (such as the persistence objects).
Product and rate data is frequently accessed but it's not updated that regularly, so it's a good candidate for caching the data instead of hitting the back-end database every time. They should be used where they are not confusing or misleading in understanding the actual code.
In the context of domain modeling, Entity, Repository and Service are good candidates for using Annotations. It offers a role-based declarative security for Java objects using MethodSecurityInterceptor class.
We can write common security rules in one place and apply them (using AOP techniques) wherever they need to be implemented. Hardcoding the complex routing or decision-making rules logic in the classes leads to longer methods in the classes, code duplication, and ultimately a rigid application design which will become a maintenance nightmare in the long run. Struts (Application layer), Spring (Service) and Hibernate (ORM) all have their own validation modules where we can apply the validation rules on the incoming or outgoing data objects. Also, the public constructors should contain only the required fields instead of a constructor with all the fields in the domain class. The core domain objects and their bitemporal properties can be persisted using an ORM product such as Hibernate.
Repositories and DAO's keep the domain model decoupled from dealing with the data access and persistence details. DAO classes should never be called directly from the client (Services and other consumer classes).
This design eventually leads to the afore-mentioned Anemic Domain Model where facade classes start accumulating more business logic and domain objects become mere data carriers. There are also the cross-entity transactions (that span multiple domain objects in the same UOW) that affect the design decision of where the transactions should be managed. Service classes should handle transactions; this way even if the transaction spans multiple domain objects, the service class can manage the transaction since in most of the use cases the Service class handles the control flow. Mapping the data from one or more domain objects to a DTO will become a necessary evil in distributed applications where sending the domain objects across the wire may not be practical from a performance and a security stand-point. This annotation is Spring specific, so other options for achieving this injection is to use something like Hibernate Interceptor. When using ROO, we define the domain model, and then the framework (based on Maven Archetypes) generates the code for Model-View-Controller (MVC), DTO's, Business Layer Facade and DAO layers. To see what tasks can be automated, let's look at a typical use case involving the domain model. These classes and XML files that have boiler-plate code and structure are great candidates for code generation. Code generation tools typically use some kind of template framework to define the templates or mappings from which a code generator can generate the code. Code generation option is a good long-term solution even though it involves some initial investment (in terms of coding and time) to build and test the code generator (engine).
Design refactoring is done to continually refine the model and refactor the code to improve the domain model. Borrower and the seller meet with the closing agent at the title company to sign the paperwork to transfer the title of the property.
Embedding this logic in the domain objects leads to tangling and cluttering of the domain layer with non-domain related code. Other aspects in the domain layer that could use AOP are caching, transaction management and role based security (authorization). He mentioned that domain objects need access to other fine grained objects to provide rich behavior and a solution to this is to inject Services, Factories, or Repositories into Domain Objects (by using Aspects to inject dependency at constructor or setter invocation time).
Spring 2.5, Hibernate 3 and other frameworks take full advantage of Annotations to configure the components in different layers of a Java enterprise application.
A good example of using Annotation is Hibernate ORM mapping where it adds value to specify the SQL table or column name right next to the class or attribute name. There is also instance level security in the form of Access Control Lists (ACL's) for domain objects to control the user access at the instance level.
This means the same domain object, in a different business context, will have to process different set of business rules. If a business rule logic spans two or more Entity objects, then it should become part of a Service class.
A good design is to place all the rules (especially complex rules that change frequently as the business strategy changes) into a Rules engine (using a rules framework like JBoss Rules, OpenRules, or Mandarax) and invoke them from the domain classes. In some cases, validation rules can also be managed as Aspects (link AOP rules article here) that can be weaved into different layers (e.g.
The clients should always call the domain objects which in turn should call the DAO's for persisting the data to the data store. A good design is to inject Repositories and Services into domain objects using DI & AOP techniques. But at the same time, the table and column names are embedded in the code which may not be a flexible solution in some cases.
Eclipse Modeling Framework (EMF) has several sub-projects that aid in the code generation of various artifacts required in a web application project. Entities and Value Objects in DDD are classic examples of OOP concepts since they have both state and behavior. On the other hand, details like JDBC driver configuration (driver name, jdbc url, user name, and password) are better suited to be stored in an XML file rather than using Annotations. For example, some attributes of a loan domain object (such as loan amount and interest rate) cannot be changed after the loan has been through the Underwriting step in the loan approval process.
Model Driven Architecture (MDA) tools like AndroMDA use EMF to generate the code based on architecture models. Imagine how much value is created by just improving the way you manage existing grape juice flavour precursors? But the same attributes can be changed when the loan is just registered and locked for a specific interest rate. If significant transformations are required between the domain model and the database tables, then the design should take that concern into consideration.



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