I am quite new with DDD and would like to know about any pitfalls you might want to share. I will summarize it later for more newbies to read :)
Thanks
Summary so far:
Anemic domain model where your entities are primarily only data bearing and contain no business logic
Not using bounded contexts enough
Focusing too much on patterns
There is a good presentation on this topic as well here (video).
Probably the most important one: not grokking the central, fundamental principle of the Domain Model and its representation in Ubiquitous Language. With the plethora of technology options around, it's very easy for your head to fill up with ORMs, MVC frameworks, ajax, sql vs nosql, ... So much so there's little space left for the actual problem you're trying to solve.
And that's DDD's key message: don't. Instead, explicitly focus on the problem space first and foremost. Build a domain model shorn of architectural clutter that captures, exposes and communicates the domain.
Oh, and another one: thinking you need Domain Services for everything you can do in the domain model. No. You should always first try to put domain logic with the Entity/Value type it belongs to. You should only create domain services when you find functions that don't naturally belong with an E/V. Otherwise you end up with the anaemic domain model highlighted elsewhere.
hth.
One of the biggest pitfalls is that you end up with a so-called anemic model where your entities are primarily only data bearing and contain no business logic. This situation often arises when you build your domain model on top of an existing relational data model and just make each table in the database an entity in your domain model.
You might enjoy presentation of Greg Young about why DDD fails.
In short:
Lack of intent
Anemic Domain Model
DDD-Lite
Lack of isolation
Ubiquitous what?
Lack of refinement
Proxy Domain Expert (Business analyst)
Not using bounded contexts enough. It's toward the back of the the big blue book but Eric Evans has gone on record as saying that he believes that bounded contexts and ubiquitous language are THE most important concepts.
Similarly, people tend to focus too much on the patterns. Those aren't the meat of DDD.
Also, if you do not have a lot of access to domain experts you are probably not doing DDD, at best you are DDDish.
More concretely, if you end up with many-to-many relationships, you've probably designed something wrong and need to re-evaluate your aggregate roots/contexts
Only adding to what others have already said;
My personal experience is that people often end up with an anemic model and a single model instead of multiple context specific models.
Another problem is that many focus more on the infrastructure and patterns used in DDD.
Just because you have entities and repositoriesand are using (n)Hibernate it doesn't mean you are doing DDD.
It's not from my personal experience with subject, but it was mentioned for a couple of times in DDD books and it's what I've been thinking about recently: use Entities when you really need identity, in other cases use Value Object. I.e., Entity pattern often happens to be the default choice for any model noun, and it's not the way it should be.
Beware of the Big Ball of Mud.
One of the pitfalls of domain driven design is to introduce ambiguity into a model. As explained in the article Strategic Domain Driven Design with Context Mapping:
Ambiguity is the super-villain of our
Ubiquitous Language
This may happen when two distinct concepts share the same name, or when the same concept can have different uses. It may be necessary to
expose the domain structure in
terms of bounded contexts in a context
map
If a model is used in too many different ways, or has too many responsibilities, it may be a sign that it should be divided.
Related
Consider certain kinds of objects involved Domain-Driven Design (DDD): Entities, Value Objects, Domain Events, and Domain Services.
Which of these are considered to be Domain Objects? And are there other names for abstractions that encapsulate a subset of those?
I can identify various abstractions that are useful to have when talking about DDD or domain models:
Entities and Value Objects. I often find myself mentioning "Entities or Value Objects". Most notably, these are the ones that model the domain's state. In contrast, Domain Services are stateless, and I would argue that Domain Events merely reflect information about how the domain came to be in its current state.
Entities, Value Objects, and Domain Events. These may all contain or represent data, whereas the Domain Services only define behavior.
All objects recognized by the domain model. It is useful to be able to talk about parts of the domain model in general, as opposed to concepts outside of it.
It's interesting how even Stack Overflow's domain-object tag has a confusing definition:
Domain Objects are objects made for dealing with the domain logic at the Model layer. These objects generally simulate real (or virtual) items from real-life: Person, Post, Document, etc.
The initial definition, focused on "dealing with the domain logic", leans towards "all objects recognized by the domain model". The examples then lean towards "Entities and Value Objects".
DDD hammers on a clearly defined, unambiguous Ubiquitous Language, and with good reason. Shouldn't it lead by example? :)
Which of these are considered to be Domain Objects?
All of them. They are "objects" that implement our domain model. In the original DDD text, Eric Evans also used the phrase "model elements".
The distinctions between them are largely a consequence of the constraints of the Java language. You wouldn't need "value objects" if you could just create bespoke values; you wouldn't need "domain services" if you could just pass around the capabilities you need. You wouldn't need "domain events" if you have "messaging" as a ubiquitous construct, and so on.
DDD hammers on a clearly defined, unambiguous Ubiquitous Language, and with good reason. Shouldn't it lead by example? :)
Well, part of the riddle is that these patterns are part of a general purpose language, and one of the central messages of DDD is that you shouldn't allow general purpose concerns to distract you from the domain itself.
That said... yeah - it would be better today if Evans had a rich understanding of these ideas eighteen years ago, and was able to introduce the best language and provide counter measures to prevent semantic diffusion.
Im new to learn DDD concept and i cant understand something.
1-What difference between Context Map and Bounded Context and SubDomain?
2-How to recognize relation between Bounded Context ?
As said in the comment, this is a wide subject, and very important in DDD. It is the strategic part of DDD. Anyway I will try to answer your questions with an overall explanation:
DDD is about understanding and distilling the domain of the problem we want to solve. It is a continuous process of learning about the domain, talking to the domain experts. All people (developers, business people, etc) speak the same language. This language is used everywhere (conversations, documentation, source code, ...). It is called the Ubiquitous Language (UL).
The problem domain may have different areas of functionality, which would be domains too. They are the subdomains. So a subdomain is a subset of the problem domain. It is like splitting the problem into smaller subproblems, and a subdomain would be the domain of a subproblem. There are 3 kinds of subdomains:
Core: The point of distillation is to discover the subdomain that has value for the business, i.e., the one that will make your product better than others of the same kind. Such subdomain is the "core subdomain". For example, in "project management", the "task assignement" would be core.
Supporting: It is specialized in some business aspect that helps the core functionality. For example, in "project management", a "calendar" (for marking tasks delivery dates).
Generic: Functionality that maybe needed by any kind of application. For example, authentication and authorization of users.
Subdomains belong to the problem space.
To solve the problem, you model the subdomains, and you create bounded contexts (BCs). In practice, a BC is an autonomous application that contains the software model of a subdomain. A BC has its own UL. It is the context on which a term of the UL has a meaning. UL and BCs are the most important things in DDD. UL drives the BCs identification.
Ideally, you should align 1:1 the subdomains of the problem space with the BCs of the solution space, i.e., you should have a BC for each subdomain.
A team can develop one or more BCs, but a BC should be developed by just one team.
BCs belong to the solution space.
Context Map: It is a drawing that shows the BCs, and the relationships among them. Every relationship is classified in one of the following patterns:
Partnership
Shared Kernel
Customer-Supplier
Conformist
Anticorruption Layer
Open Host Service
Published Language
Separate Ways
Big Ball of Mud
Recognizing which pattern to apply in a relationship it will depend on the particular case you have. Some things that you have to consider are:
The 2 teams collaborate together.
One of the teams doesn't care about the other one.
The teams can negotiate.
The teams are independent.
Changes on a model (upstream) affects to the other model (downstream).
As #Augusto mentioned, this is a couple of chapters in the blue book, but here goes.
The domain model is found in the business rules and how people talk but a simplification of it is captured in code. Certain naming is consistent and the necessary invariants are enforced in the model.
A bounded context is mostly conceptual (might be a namespace, module, project in code as well...). It is the intention to keep a domain model consistent within it. So within the context, a certain ubiquitous language is used. And a model need only serve the needs of THAT context. It is the boundary in which the model can be used. In terms of recognizing these relationships? Some might be subtle but most are not. At least some people in the team will want to "avoid duplication" by unifying the model... so that is a clear indication that there is a relationship. Names are often the same or similar... or could be the same but one is better suited to one domain and another to another domain.
A context map is a bit more of a project management tool. It is a map of how different contexts (and the models within) relate to each other. In an Ordering Domain in an e-commerce system you may have a product. It would lead to A LOT of complication trying to have a unified Product in a model that spanned Ordering, Payments, Content for the website and Inventory domains (for example). So each of those domains should have a separate model. The context map is a diagram and related documentation that relates these bounded contexts together since there would be relationships and translation of data across from one model to the next, as an order flows through the system.
The last element you asked about is a subdomain. Here you probably are referring to a generic subdomain. Personally, I think the name is a little confusing. It makes it seem like a subset of the model. Maybe this is on purpose but I generally think of them as their own domain, just one that is not central to the business's proposition. For instance, if the aforementioned e-commerce company was known for its same day or next day delivery, then they probably shouldn't buy an off-the-shelf solution to inventory and shipping management. On the other hand, if they were focusing on a market that just wanted the cheapest deal but didn't mind waiting a few days, then that would be a perfect candidate for a generic subdomain.
My DDD glossary which has plenty of links at the bottom to more detailed articles.
If you are serious about learning this subject and can get your hands on some books:
Domain-driven Design by Eric Evans
Implementing Domain-driven Design by Vaughn Vernon
Domain-driven Design made functional by Scott Wlaschin (my favourite)
One common reaction that I see for a lot of questions asked here and other forums are like "You don't need to do DDD for that. Its a simple CRUD application, DDD is an over-engineering".
Well I am new to DDD and I feel there are a lot of elements in DDD that has universal appeal and can be used across the board, irrespective of the fact whether your application is complex enuf to mandate DDD. For example, layering of application, differnent artifacts that DDD recognises etc. May be start with the basics and admittedly anemic models and then work/refactor towards as much purity as one can get.
Does this approach sound good?
Or would you say that there is a fundamental choice in design of every application in terms of whether to go DDD way or not , kind of "all-or-none" choice?
UPDATE (to provide more context, in response to hugh's comment below)
I am building a webapp around an existing RuleEngine kind of application, basically CRUD and some validations, invariants and then a process of deployment. The rule-authoring and semantic check is done by a standalone piece of code that i call as part of the CRUD and none of that semantic specific logic is there in my code. I am trying to use DDD for this application, but i see it might not be complicated enough to fit into the DDD paradigm. There is no ubiquitous language defined for the domain i.e the language is not specialized enough beyond naming the set of entities involved. I hear my domain expert speaking in terms of creating, editing, deleting entities.
DDD is not all-or-nothing. Also, many of the patterns described in DDD are not new and can be found all over the place. Eric Evans (the author of the DDD book) just assembled them, formalized them where needed, and set them in relation to each other. You are free to use what fits to your problem space.
What is often overlooked: DDD describes implementation patterns as well as analysis patterns. The analysis patterns may be overkill in many (if not most) applications, but the implementation patterns (i.e. Entities, Specifications, Services) can be of great use in less complex scenarios as well.
In short,
If it's just CRUD, I wouldn't bother.
On the other hand,
If it's got behavior, where the next state of something relies on the previous state, then DDD is something you probably want to consider.
DDD approach is based on two type of patterns: Strategics patterns and Tactical patterns. IMHO, be free to use tactical patterns in every case that you sure can be helpful. But using Strategic patterns can be overkill for some type of domains. If CRUD style thinking, does not have negative impact in modeling process, certainly you doesn't gonna need it.
I'm really new to DDD and trying to grasp some of the concepts.
Could someone explain me the idea behind Domain Modeling in DDD.
I have already gone through wikipedia explanation: http://en.wikipedia.org/wiki/Domain_model but still seems like there are some gray areas in my understanding.
Based on what I understood, domain modeling involves building a model around the business entities to express their relationships, express the entities that participate in the model etc..
Isn't this something that has been in practice always? in Object Oriented world, you model business entities into classes, objects etc.. and build the software around this.
What I do not understand is the emphasis Domain Modeling gets in DDD. Is it the same object/class modeling that you find in OO world, or is this something new to DDD ?
How does it differ from Object Oriented design/modeling?
Your answers are highly appreciated.
One distinction is that a "proper" implementation of the Domain Model Pattern in DDD is isolated from cross-cutting concerns.
For example, it contains nothing to do with databases or other persistence. Where it contains validation logic, it is business validation, not "does the name exceed the column length?" validation.
The idea is that the domain model encapsulates "the business" -- in business terms ("ubiquitous language"), to the extent possible -- and exposes relevant aspects of the business to "the program" without acquiescing to the needs of the software.
On the flip side, "the software" is concerned with IO, UI, and the like, but delegates all business logic to the domain model.
In principle, you can wrap your domain model up in an assembly and use it across multiple applications. When business rules change, as they do, you have one very logical place in which to affect the changes (because the model is a 1:1 or nearly-so representation of the relevant aspects of the business and is described in the same terms as the business).
The Domain in DDD does not need to be implemented in OO. In my experience an OO domain model is usually best, but there are very valid examples of situations in which it may not be.
You might implement a domain in rules, with a rule engine (example in The Netherlands where this is done for a large mortgage application). Or you might do it in a functional language. The essence is that your domain, in however fashion it is implemented, is isolated from what I usually call the technical aspects of your application (or, as the previous answer calls it, cross-cutting concerns, although I think there may very well be cross-cutting concerns within a domain). An isolating layer, which may be implemented using adapters, makes the domain as much as possible, even completely, independent from the technicalities. This layer usually leverages patterns such as Facade and Observer.
I've always developed code in a SOA type of way. This year I've been trying to do more DDD but I keep getting the feeling that I'm not getting it. At work our systems are load balanced and designed not to have state. The architecture is:
Website
===Physical Layer==
Main Service
==Physical Layer==
Server 1/Service 2/Service 3/Service 4
Only Server 1,Service 2,Service 3 and Service 4 can talk to the database and the Main Service calls the correct service based on products ordered. Every physical layer is load balanced too.
Now when I develop a new service, I try to think DDD in that service even though it doesn't really feel like it fits.
I use good DDD principles like entities, value types, repositories, aggregates, factories and etc.
I've even tried using ORM's but they just don't seem like they fit in a stateless architecture. I know there are ways around it, for example use IStatelessSession instead of ISession with NHibernate. However, ORM just feel like they don't fit in a stateless architecture.
I've noticed I really only use some of the concepts and patterns DDD has taught me but the overall architecture is still SOA.
I am starting to think DDD doesn't fit in large systems but I do think some of the patterns and concepts do fit in large systems.
Like I said, maybe I'm just not grasping DDD or maybe I'm over analyzing my designs? Maybe by using the patterns and concepts DDD has taught me I am using DDD? Not sure if there is really a question to this post but more of thoughts I've had when trying to figure out where DDD fits in overall systems and how scalable it truly is. The truth is, I don't think I really even know what DDD is?
I think a common misconception is that SOA and DDD are two conflicting styles.
IMO, they are two concepts that work great together;
You create a domain model that encapsulates your domain concepts, and expose entry points into that model via services.
I also don't see what the problem is with ORM and services, you can easily use a session/uow per service call.
Just model your service operations as atomic domain commands.
a naive example:
[WebMethod]
void RenameCustomer(int customerId,string newName)
{
using(var uow = UoW.Begin())
{
var customerRepo = new CustomerRepo(uow);
var customer = customerRepo.FindById(customerId);
customer.Rename(newName);
uow.Commit();
}
}
Maybe the problem you are facing is that you create services like "UpdateOrder" which takes an order entity and tries to update this in a new session?
I try to avoid that kind of services and instead break those down to smaller atomic commands.
Each command can be exposed as an operation, or you could have a single service operation that receives groups of commands and then delegate those to command handlers.
IMO, this way you can expose your intentions better.
The most important things about Domain-Driven Design are the big picture ideas:
the ubiquitous language,
the strategic decision-making where you are adding value by working in the core domain (and insulating yourself from other nasty systems), and
the approach to making testable, flexible designs by uncoupling infrastructure from business logic.
Those are broadly applicable, and are the most valuable pieces.
There is a lot of design-pattern stuff about Factories, Services, Repositories, Aggregates, etc., I take that as advice from one experienced developer to another, not as gospel, because so much of it can vary depending on the language and frameworks that you're using. imho they tend to get overemphasized because programmers like us are detail-oriented and we obsess on that kind of stuff. There is valuable stuff there too, but it needs to be kept in perspective. So some of it may not be that relevant to you, or it might grow on you as you work with it.
So I would say it's not like there's a checklist that you can run through to make sure you're using all the patterns, it's a matter of keeping the big picture in mind and seeing how that changes your approach to developing software. And if you pick up some good tips from the patterns that's great too.
Specifically with respect to the SOA thing, I've developed applications that defer all their state to the database, which have used persistence-ignorant domain objects. Writing tests for services that have to mock daos and feed stuff back is drudgery, the more logic I can put in the domain objects the less I have to mess with mocks in my services, so I tend to like that approach better.
There are some concepts introduced with DDD which can actually confuse you when building SOA.
I have to completely agree with another answer, that SOA-services expose operations that act as atomic commands. I believe that a very clean SOA uses messages instead of entities. The service implementation will then utilize the domain model to actually execute the operation.
However there is a concept in DDD called a "domain service". This is slightly different than an application service. Typically a "domain service" is designed within the same ubiquitous language as the rest of the domain model, and represents business logic that does not cleanly fit into an entity or value.
A domain service should not be confused with an application service. In fact, an application service may very well be implemented such that it uses a domain service. After all, the application services can fully encapsulate the domain model within SOA.
I am really really late in this, but I would like to add the following in the very good answers by everyone else.
DDD is not in any conflict with SOA. Instead, DDD can help you maintain a better Service Oriented Architecture. SOA promotes the concept of services, so that you can define better boundaries (oh, context boundary is also a DDD concept!) between your systems and improve the comprehension of them.
DDD is not about applying a set of patterns (e.g. repository, entities etc.). DDD is mostly about trying to model your software, so that all the concepts (i.e. classes in case of object-oriented programming) align directly with concepts of the business.
You should also check this video (especially the last 5 minutes), where Eric Evans discusses exactly this topic.
I've even tried using ORM's but they just don't seem like they fit in
a stateless architecture.
I don't have any reference handy to back this up. However, you're right, ORMs do not fit nicely with DDD as well. This is because, they're trying to bridge the object-relational impedance mismatch, but in a wrong way. They force the software towards an anemic domain model, where classes end up being "plain data holders".
I am starting to think DDD doesn't fit in large systems but I do think
some of the patterns and concepts do fit in large systems.
In the video I've linked above, you can also find Eric explaining that DDD concepts can "break" in very large-scale systems. For instance, imagine a retail system, where each order is an aggregate containing potentially thousands of order items. If you'd like to calculate the order's total amount strictly following DDD, you'd have to load all the order items in memory, which would be extremely inefficient compared leveraging your storage system (e.g. with a clever SQL statement). So, this trade-off should always be kept in mind, DDD is not a silver bullet.
Like I said, maybe I'm just not grasping DDD or maybe I'm over
analyzing my designs?
Excuse me, but I'll have to quote Eric Evans one more time. As he has said, DDD is not for perfectionists, meaning that there might be cases, where the ideal design does not exist and you might have to go with a solution, which is worse in terms of modelling. To read more around that, you can check this article.