I defined quickly my domain model in UML (on paper) and as I start to test drive out functionality, refactoring has led me to small classes that do no represent concepts in my domain but these classes nicely encapsulate the responsibility needed.
For example, I started with a Machine which has a number of licenses (Machine --->* License). I started with methods Add(licenseType) and remove(licenseType) which increased or decreased the corresponding license object in the list (i.e. license has a licenseType and a counter of the number of licenses of that type).
Machine has other associations and behaviors so I created a LicenseTypeManager where I now have Machine --->1 LicenseTypeManager --->* License.
I have Machine as an aggregate root, LicenseTypeManager as a Value object and License as a Value object.
Now LicenseTypeManager is something I created whilst refactoring and was not mentioned at all and is not part of the ubiquitous language of the application. Is it okay for it to exist?
In other words is it fine to model using UL and then find other terminology that may help in explaining the domain more clearly?
Also, I started to think that LicenseTypeManager could be a domain service but then I started to worry that I may be creating an anemic model (although there is still a lot of logic in the model). So my next question is should it be a domain service or should it remain where it is?
JD
It doesn't matter what causes enrichment of ubiquitous language. But it matters that it is ubiquitous.
So - if you model your domain and figure out new terms that eases understanding, there's nothing wrong with that as long as domain experts understands them, already uses or starts using them too.
Imagine you are selling cars and know nothing about programming.
Would Car type manager make any sense to you? Unlikely. It should not live in domain either.
As I see it:
- you don't understand distinction between aggregate roots, entities and value objects
- you lack knowledge of OOP in general (hence you seek for redemption through introduction of "managers")
Related
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)
What are DDD recommendations for inter-domain referencing design?
Should I try to connect them as "Matryoshka" (put one into another) or it is better to create upper-level "inter-domain" business service?
P.S. Crossing this smooth water, I was unable to find anything useful to read in the Internet, and have started thinking that for this kind of things exist better term than "inter-domain referencing"... Am I right?
DETAILS:
I have two models/business services.
Semantically first domain (A) is CRM with sell/maintenance process for our goods, second domain (B) is "design" data of our goods. We have two view points on our goods: from seller perspective and from engineer perspective.
Actually each model is effective ORM (Object-Relational Mapping) tool to the same database.
There are some inter-domain activities e.g. validations (e.g. sometimes we can sell things to smb. only if some engineering rules are valid).
From developer's point of view I have two clear possibilities (reference B in A or create new cross reference domain/service C ). But from designer perspective I am lost in understanding what kind of Business Service I have when I compose business logic from two different domains.
As far as I know, DDD has no strict rules for 'inter-domain' referencing. At the end of the day your domain model will have to reference basic Java or .NET classes. Or it may reference specialized date/time or graph library (aka 'Generic Domain').
On the other hand DDD has a concept of Bounded Context. And it has quite a few patterns that can be applied when you work at the boundaries of the system. For example 'Anticorruption Layer' can be used to isolate you from legacy system. Other integration styles can be used depending on how much control you have over external code, team capabilities etc.
So there is probably no need to introduce artificial glue layer if you just dealing with two subdomains in one Bounded Context. Might also be worth reading Part 4 of DDD book (Strategic Design).
UPDATE:
Based on the information you provided, it looks like you only have one Bounded Context. You don't seem to have 'linguistic clashes' where the same word have two different meanings. Bounded Context integration patterns are most likely not applicable to your situation. Your Sales domain can reference Products domain directly. If you think of Products domain being more low-level and Sales being high level you can use Dependency Inversion Principle. Define an interface like ProductCompatiblityValidator in Sales and implement it in Products domain. And then inject the actual implementation at the application layer. This way you will not have a direct reference from Sales to Products.
In addition to what Dmitry has already said...
I think of any code that crosses bounded contexts as application layer code. I would have that application layer code reference domain types from both contexts (and their repositories) but not have two domains reference each other. I think it's OK to have business logic in an application layer if it specifically crosses domain boundaries and is unit-testable.
If you really have a hierarchy, then it would be OK to have the the more concrete subdomain reference the more abstract domain. However, I would be careful if this causes you to need to have domain objects reference repositories of any type. Pulling objects out of of a repository is rarely a true domain concept. Referencing repositories is best done in an application layer that sits a layer above the domain model.
Of course this is all as much art as science. I'd try modeling a thin slice of your application a couple different ways and see what friction you run into with each approach.
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.
I am on a tight schedule with my project so don't have time to read books to understand it.
Just like anything else we can put it in few lines after reading books for few times. So here i need some description about each terms in DDD practices guideline so I can apply them bit at a piece to my project.
I already know terms in general but can't put it in terms with C# Project.
Below are the terms i have so far known out of reading some brief description in relation with C# project. Like What is the purpose of it in C# project.
Services
Factories
Repository
Aggregates
DomainObjects
Infrastructure
I am really confused about Infrastructure, Repository and Services
When to use Services and when to use Repository?
Please let me know if anyway i can make this question more clear
I recommend that you read through the Domain-Driven Design Quickly book from infoq, it is short, free in pdf form that you can download right away and does its' best to summarize the concepts presented in Eric Evan's Blue Bible
You didn't specify which language/framework the project you are currently working on is in, if it is a .NET project then take a look at the source code for CodeCampServer for a good example.
There is also a fairly more complicated example named Fohjin.DDD that you can look at (it has a focus on CQRS concepts that may be more than you are looking for)
Steve Bohlen has also given a presentation to an alt.net crowd on DDD, you can find the videos from links off of his blog post
I've just posted a blog post which lists these and some other resources as well.
Hopefully some of these resources will help you get started quickly.
This is my understanding and I did NOT read any DDD book, even the holy bible of it.
Services - stateless classes that usually operate on different layer objects, thus helping to decouple them; also to avoid code duplication
Factories - classes that knows how to create objects, thus decouple invoking code from knowing implementation details, making it easier to switch implementations; many factories also help to auto-resolve object dependencies (IoC containers); factories are infrastructure
Repository - interfaces (and corresponding implementations) that narrows data access to the bare minimum that clients should know about
Aggregates - classes that unifies access to several related entities via single interfaces (e.g. order and line items)
Domain Objects - classes that operate purely on domain/business logic, and do not care about persistence, presentation, or other concerns
Infrastructure - classes/layers that glue different objects or layers together; contains the actual implementation details that are not important to real application/user at all (e.g. how data is written to database, how HTTP form is mapped to view models).
Repository provides access to a very specific, usually single, kind of domain object. They emulate collection of objects, to some extent. Services usually operate on very different types of objects, usually accessed via static methods (do not have state), and can perform any operation (e.g. send email, prepare report), while repositories concentrate on CRUD methods.
DDD what all terms mean for Joe the plumber who can’t afford to read books few times?
I would say - not much. Not enough for sure.
I think you're being quite ambitious in trying to apply a new technique to a project that's under such tight deadlines that you can't take the time to study the technique in detail.
At a high level DDD is about decomposing your solution into layers and allocating responsibilities cleanly. If you attempt just to do that in your application you're likely to get some benefit. Later, when you have more time to study, you may discover that you didn't quite follow all the details of the DDD approach - I don't see that as a problem, you proabably already got some benefit of thoughtful structure even if you deviated from some of the DDD guidance.
To specifically answer your question in detail would just mean reiterating material that's already out there: Seems to me that this document nicely summarises the terms you're asking about.
They say about Services:
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.
Therefore: 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.
Now the thing about this kind of wisdom is that to apply it you need to be able to spot when you are "distorting the definition". And I suspect that only with experience (or guidance from someone who is experienced) do you gain the insight to spot such things.
You must expect to experiment with ideas, get it a bit wrong sometimes, then reflect on why your decisions hurt or work. Your goal should not be to do DDD for its own sake, but to produce good software. When you find it cumbersome to implement something, or difficult to maintain something think about why this is, then examine what you did in the light of DDD advice. At that point you may say "Oh, if I had made that a Service, the Model would be so nmuch cleaner", or whatever.
You may find it helpful to read an example.:
I am fairly new to this discussion but I HAVE to ask this question even at the risk of sounding 'ignorant'. Why is it that we now stress so much on 'DDD'. The more I look into 'DDD' the more complex it seems to make my application. Whereas modeling my domain with the database helps keep my application consistent across layers. Then I can use DAL Helpers such as SubSonic or L2S to easily access that model. What is so bad about this? Even in enterprise applications?
Why do we strive to create a new way of modeling our domain when we have a tried and tested one?
I am willing to hear from the purists here.
You can't sell an old methodology, because too many projects failed and too many people know the old methodology anyway. There has to be a new one to market.
If you're doing fine with the old way then use what works. Do pay attention to new stuff, as some really nice ideas come along. But that doesn't mean everything old is bad and stupid. Usually you can incorporate new ideas into the old models to a large degree.
There does come a time to make a move. Like I wouldn't do OOP with structures and function pointers. ;-)
This is actually a really excellent question, and the short answer is "you can." We used to do it that way, and there was a whole area of enterprise (data) modeling. In fact, the common OOD notations evolved from ERD.
What we discovered, however, was that data-driven designs like that had some difficulties, the biggest of them being that the natural structure for a data base doesn't necessarily match well to the natural structure for code.
OOD, to a great extent, derives from the desire to make it easier to find a code structure that has a couple of desirable properties:
it should be easy to think out the design
it should be robust under changes.
The ease to think out design comes originally from Simula, which used what we now think of as "objects" for simulation specifically; it was convenient in simulation to have software entities that correspond to the things you're simulating. It was only later that Alan kay et al at Xerox saw that as a more general structuring method.
The part about robustness under changes had many parents, but one of the most important ones among them was Dave Parnas, you wrote several papers that identified a basic rule for modularization, which I call Parnas' Law: every module should keep a secret, and that secret is a requirements that is likely to change.
It turns out that by combining Parnas' Law with the Simula idea of a "object" as corresponding to something that can be identified with the real world, you tend to get system designs that are more robust under requirements changes than the old way we did things. (Not always, and sometime you have to be crafty, as with the Command pattern. Most objects are nouns, thing that have persistent existence. In the Command pattern, the ideal objects are verbs, things you do.)
However, it also turns out that that structure isn't necessarily a good way to represent the underlying data in a relational database, so we end up with the "object relational impedance mismatch" problem: how to represent the transformation from objectland to database-land.
Short answer: if all you need is a CRUD system that allows users to edit data, just build an Access front-end to your back-end database (or use a scaffolding framework like you mentioned) and call it a day. You should be able to lop off 70% of your budget vs. a domain-driven system.
Long answer: with a data-driven design, what does the implementation of the business model look like? Usually after a couple years of building on new features to your application, you'll find that it's all over the place: tables, views, stored procedures, various application services, code-behind files, presenters/ViewModels, etc. with duplication everywhere. When you're having a conversation with the domain expert about a new feature they are requesting, you are constantly trying to translate from the business language into the language around your implementation, and it just does not translate.
What typically ends up happening is that you are forced to communicate with the business in terms of the implementation of the system, and the implementation becomes the "ubiquitous language" that the business and developers are forced to use when communicating. This has a wide range of consequences. The domain experts in the business start believing that they are experts in the implementation domain, and they start demanding features in terms of implementation rather than the business need they are trying to solve.
Also, you'll find that most data-driven implementations do not follow the "conceptual contours" of the domain, and the components of the system aren't very flexible in how they can be combined together to solve the problem, because they don't map one-to-one with concepts in the business model. When code isn't cohesive, changes and new features may require modifications all over your implementation.
Domain Driven-Design provides tools for making your implementation so closely resemble the business model that it's easy for everyone to speak the language of the business. It allows you to write "executable specifications" that test your implementation, but can actually be understood by your domain experts.