What are the key differentials between the shared-kernel and published-language strategic patterns opted in Domain driven design (DDD)?
Both shared-kernel and published-language are part of the Context Maps patterns collection. Context Mapping is a very useful and powerful tool that allows one to see what kind of dependencies link systems together. They can also highlight teams relationships.
A shared-kernel means that 2 systems are strongly coupled by sharing a shared artifact (model, DLL, Jar, DB, ...). If those 2 systems are handled by 2 different teams, it means that whenever Team A change something, it will impact Team B and vice versa.
A published-language is a model that is well documented that everyone can understand and translate. Think of iCal, VCard or such things.
Michael Plöd did a great job on documenting Context Maps patterns, you can have a look here.
They are completely different things.
Shared kernel basically is a model shared by two bounded context.
Published language often goes together with the open host service pattern, and is a well known language, used to define the offered services. For example, JSON or XML.
Related
My question here is quite straight as mentioned in the subject.
However, please allow me to give some brief explanation here about my innocent thoughts.
I've been using Axon for approximately 10 months now. I used to design my project structure based on the Hexagonal architecture with two top level packages respectively for domain and infrastructure.
Furthermore, domain package will contain different domain objects (as explained in the DDD concept) such as follow:
Aggregate (this will be an Axon aggregate class).
Repository (in my case, this will be a Spring Data Repository interface).
Entity (in my case, this contains any lookup entity that i used for set-based consistency validation as written here).
Service Port (collection of Input and Ouput port interfaces).
Commands (representing Axon Command object).
As for Events, I used to put them on a different module that I compiled as a jar file, so I can share it to other developers whom going to use the same event in their project.
I've noticed recently that all of my commands and events were basically anemic models (an anti pattern that we should avoid).
Is there any good practice on this ? Or, Is it something that intentionally used by design ?
I've been thinking to put my Command classes within my Aggregate class (as an inner classes). At least by using this approach I won't end-up with having so many anemic models scattered outside. Any thoughts ?
Commands are designed to be behavior and input structures mirroring the external world. They don't necessarily mirror an aggregate's structure.
They are not even connected clearly to one single aggregate, at times. Enclosing them within aggregates can be a code smell because you are then thinking in terms of resources and UI organization, instead of transaction boundaries and entity groups.
You are also violating the open-closed principle. Changes in volatile layers like user interface and request structures will make you edit the Aggregate class, and that is not good design.
On a more general note...
At times, this debate of anemic vs. non-anemic (or dry vs. non-dry) can push you in the direction of premature - and incorrect - optimization. Try avoiding this trap because you will end up optimising at the code level, but your domain will suffer.
DDD and CQRS guidelines align with principles that help you keep complexity at bay over the long term. Things kept distinct and separate help you achieve this.
First of all, in DDD, your domain had to be free of any frameworks, just use pure language library.
Then, mixing Commands and Aggregates cannot be a good solution. I think Commands belongs to Port while Aggregates belongs to the Hexagone.
Finally, DDD highlights the discovery of the domain thanks to the experts. Did you do that ? If not, if you're only using the Tacticts pattern, you'll miss one of the most important part of DDD.
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've just begun to delve into my first experiments with Domain Drive Design and I'm taking advantage of the NWorkspace pattern. This pattern seems to make a lot of sense however I haven't been able to find very many examples of places this pattern has been successfully used or even publicly documented. Before I get to far into my implementation I would like to know if anybody has had success using this pattern or whether somebody could point me to any references where NWorkspace has been used in any open source project that I could learn from. Also are there better or more well known alternatives to this pattern that I should know about?
Brief background on NWorkspace
For those who may not be familiar with NWorkspace, it is a pattern introduced by Jimmy Nisson's which abstracts query and persistance responsibilities. In his book Applying Domain-Driven Design and Patterns, Jimmy Nilsson shows how NWorkspace can be used to abstract the infrastructure portions of a DDD Repository as well as provide a mechanism to perform cross Repository atomicity with regard to persistence.
It seems like he's recommending separate interfaces for read and write repositories.
I don't have experience with the pattern described, but I would recommend not having cross-repository transactions. Instead, I would suggest a few solutions popular amongst the DDD community (Eric Evans, Udi Dahan, Greg Young) that have really helped me:
Always use eager loading on your aggregate roots. Then you don't need cross-repository atomicity, and figuring out what's changed when you persist the object is a lot easier.
Use separate classes for writing (i.e. domain classes) and reading (i.e. your viewmodel). Create view model repositories that retrieve viewmodels directly from the database (instead of mapping domain objects to view model classes).
See if implementing the above 2 things simplifies your design.
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.