I run across Orika recently.
And I couldn't find a good explanation of why I should use it. If I have, say, a User domain object, why not use that? Why do I need to create a UserDTO with more or less the same members.
Of course there are times when I need to hide some fields. But that doesn't explain the need to have dozens of libraries.
Can someone explain to me why I should not re-use domain objects from one architectural boundary to another? Saying boundary to include layers or micro-service interfaces or anything similar.
It all depends! Good designpatterns for big systems are often overkill for smaller ones. Is the data you are getting really the same as your logical intuitive domain objects or are there extra data there.
Do you find yourself in the situation described in the answer to this post, then DTO it up. DTO's exist to limit the amount of expensive network operations by transmitting more data in each request. Say you have 'User' and 'AddressDetail' domain objects, and that you could get the data for both these objects in a single call(and the data is useful in the same area of the application) then you'd use a dto and send all the data at once.
It can be hard predicting how your system will grow(especially if you are working against a living API which someone else controls), and data transfer object on some level provides a clear separation of responsibility which is often a good thing.
I'd say reuse domain objects with caution in large systems.
Related
For my application, I am looking at using an ORM and currently trying to decide if the domain layer should interface with it through a Data Access Object, Repositories, or something else? I am hesitant to pair an ORM with repositories because they can become redundant if the ORM entities are identical with the domain objects, but having one big DAO seems cludgy. I want to keep my SQL centralized, but I can't figure which of these options, if any, would make the most sense. Any suggestions on an appropriate design pattern?
This is very opinion-based, but I tend toward creating separate entities from my domain models. The domain model needs to closely match your domain, whereas your entities need to closely model your storage. They may initially match very closely, and seem really redundant, but they very often drift dramatically from each other very quickly.
That being said, wrappers that do nothing but map domain entities to persistence entities often feels horrible, and a giant waste of time. Additionally, it doesn't pay off until much later in the game, when you are doing refactoring, and you realize that your domain isn't quite right, but you don't want to modify your persistence layer.
The good news is, most languages/frameworks have some form of a mapping library that will let you automatically map from one object to another that is similarly structured. This is a great way to speed this up initially, while still giving yourself flexibility to create a manual mapping when the requirements change out from under you.
In the Vaughn Vernon's Domain-Driven Design Distilled book we can read that we should try to avoid creating technical abstractions that are perhaps too abstract and try to be more explicit by sticking to the concepts of the Ubiquitous Language.
Where I work we've built several tracking applications and in almost every of them there is the problem of having multiple specializations of the same thing, most likely with common behaviors, but different data and validation rules.
For instance, imagine an incident logging application where various kind of incidents are reported over the phone (e.g. car accident, fire, robbery). The information gathering process is similar to every incidents, but the captured data may vary widely as well as the validation rules that constrains this data.
So far, we have always solved these kind of problems with very technical abstractions (this is an oversimplified model, but you should get the idea):
As you can see, the DataValidationRules, DataFields and DataEntries abstractions have very little to do with the business of incident logging. Actually, they are part of a very generic solution to the problem of representing multiple entity specializations with different data in any domain.
I'd like to move away from this kind of very abstract model, but at the same time I do not see what would be the correct approach in making the business concepts explicit. I understand that the answer would be different in every domain, but in essence, should I be looking into having a single class per specialization? E.g. CarAccidentIndicent, FireIncident and RobberyIncident?
With a very limited number of specializations it seems like it could be manageable, but what if I have hundreds of them?
What about the UI? That means I'd have to move away from a generic way of generating the UI as well.
After thinking a little more about it I think I may have found a better and simpler way to express my concerns when it comes to DDD, OO and modeling many specializations.
On the one hand I want to come up with a model that is faithful to the Ubiquitous Language (UL) and model domain concepts explicitly. On the other hand I'm trying to respect the "favor composition over inheritance" mantra I'm so used to apply.
It seems that boths are conflicting because in order to enable composition I'll have to introduce abstractions that are most likely not part of the UL (e.g. Entity--Field composition) and when it comes to explicit modeling I do not see any other way than inheritance with one class per specialization.
Am I wrong in trying to avoid inheritance to represent hundreds of specialized entities that mainly differ in terms of data structure, not behaviors?
Then again, assuming they did differ a lot in terms of behaviors as well I'd have the same dilemma.
Just to be more explicit on the design choices:
In one scenario, composition would be achievable dynamically without requiring multiple classes per specialized compositions:
class Incident {
Set<Detail> details;
IncidentType type;
}
interface Detail {
public DetailType type();
}
class SomeDetail implements Detail {
...
}
class SomeOtherDetail implements Detail {
...
}
In the other scenario compositions are static and do require one class per specialized composition:
class CarAccidentIncident extends Incident {
SomeDetail someDetail;
SomeOtherDetail someOtherDetail;
}
class SomeDetail {}
class SomeOtherDetail {}
Obviously, the second approach is more explicit and offers a natural home for specific behaviors and rules. In the first approach we would have to introduce some abstract and technical concepts like Operation and DetailValidation which may not align well with the UL.
With a small number of different specializations I'd probably choose the latter without a second though, but because there are many of them it seems like I'm leaning more towards dynamic composition (even thought being dynamic is not required). Should I?
When to use DDD?
The thing is, DDD is not necessarily the right fit for all systems. It's particularly well suited to large systems with complex business rules.
If the business rules that need expressing to capture the essence of a FireIncident are simple enough to be encoded in a DataValidationRules record and a set of DataFields, then that suggests that perhaps those rules do not require the complexity of a DDD implementation.
The Domain of Data Validation
However, if you acknowledge that, you can shift your perspective towards intending to actually build a pure data validation engine. The domain of data validation should include entities such as data validation rules, and data fields, and would contemplate such questions related to the lifecycles of rules and fields - e.g. 'what happens if a validation rule changes - do all existing records that have previously been validated need revalidation?'
If the lifecycle of a data validation rule itself is complex enough to warrant it, then by all means, use DDD to implement that domain, although you may still choose to use CRUD if you find there are no complex rules or processes in the domain of data validation.
Who are your Domain Experts?
The further consequence of that is that your domain experts are no longer your end users (the people who know about car accidents and fire incidents) they are now the people (most likely specialists) who craft the validation rules and fields. If using DDD, you need to be asking them what types of rules they need and how they need the rules to work, and implementing using the Ubiquitous Language that they use to talk about the art and process of crafting validation rules.
Those people, in turn, would be 'programming' a next level system (you might say they are using a 4GL language tailored to the domain of incident logging) using your data validation engine. The thing is, their domain experts would be the people who know about car accidents. But the specialists wouldn't strictly be using DDD to craft the rules of a car accident, because they would not be expressing their model in software, but in the constrained language of your data capture and validation engine.
Additions following Update
Have been pondering this since your update and had a few more thoughts/questions:
Data Validation vs Entity Lifecycle/Behavior
Most of your concern is around representing data validation rules on create/update. Something that would help to understand is - what behavior/rules are represented by your entities other than data validation? i.e. in an incident management system, you might track an incident through a set of states such as Reported, WaitingForDispatch, ResponseEnRoute, ResponseOnSite, Resolved, Debriefed? In an insurance system you might track Reported, Verified, AwaitingFunding, Closed, etc.
The reason I ask, is that in the absence of such lifecycle behavior - if the main purpose of your system is pure data validation, then I return to my original thought of wondering if DDD is really the right approach for this system, as DDD brings greatest value when there is complex behavior to be modelled.
If you do have such lifecycles or other complex behavior - then one possibility is to consider the approach from the perspective of different bounded contexts - i.e. have one bounded context for data validation - which uses the approach you've described with more technical abstractions - as it is an efficient way to represent the validations - but another context from the perspective of lifecycle management, in which you could focus more on business abstractions - if all incidents follow similar set of lifecycles, then that context would have a much smaller number of specific entities.
Keeping entities sync'd between contexts is a whole 'nother topic, but not too troublesome if you adopt a service bus or event type technology and publish events when things change.
Updates to Validation Rules?
How do your business experts express requests for changes to validation rules? And how do you implement them? I'm guessing from what you've said, they probably express them in domain terms such as 'FireIncident'. But the implementation is interesting - do you have to craft data modification statements in SQL which get applied as part of a deployment?
Inheritance vs Composition
It seems that boths are conflicting because in order to enable composition I'll have to introduce abstractions that are most likely not part of the UL (e.g. Entity--Field composition)
I do not think this is true - composition does not have to require introducing technical abstractions. With either composition or inheritance, the goal is to distil insights into the domain to discover common patterns.
e.g. look for common behaviours or data validation sets and find the business language term that describes this commonality. e.g. You might find RobberyIncident and FireIncident both apply to Buildings.
If using inheritence you might create a BuildingIncident and RobberyIncident and FireIncident would extend BuildingIncident.
If using composition, you might create a valueobject to represent a Building and both RobberyIncident and FireIncident would contain a Building property. However RobberyIncident would also contain a Robbery property and FireIncident would also contain a Fire property. CarAccidentIncident and CarRobberyIncident would both contain a Car property, but CarRobberyIncident would also contain a Robbery property of the same type as the Robbery property on RobberyIncident - assuming they are truly common behaviours.
You may still have hundreds of classes representing specialised incident types, but they are simply composed of a set of value object properties representing the set of common patterns they are composed of - and those value objects can and should be in terms of ubiquitious language concepts.
My take on this is that not all information is pertinent to the domain.
I think that in many instances we try to apply techniques in an "all-or-nothing" approach whereas we may need to be focusing on the "right tool for the job". In the answer provided by Chris he asks the question "When to use DDD?" and mentions "The thing is, DDD is not necessarily the right fit for all systems." I would argue that DDD may not be appropriate for some parts of a system.
Would DDD be useful to create, say, a word processing application? I don't really think so. Although some good old proper OO would go a long way.
DDD is absolutely great for business behaviour focused bits of a system. However, there are going to be bits that can be modeled in a more technical/generic way that feed into more interesting business functionality. I'm sure that those incidents end up in some business process. An example may be a Claim. The business is very interested in tracking a claim and the claim amount, but where that claim came from isn't all too interesting. For all intents and purposes the "initiating documentation" may be filled in using pen and paper and scanned in to be linked to said claim. One could even start a new claim on the system using a plain text input.
I have been involved in a number of systems where a lot of peripheral data was sucked into the system but actually it wasn't really contributing much (law of diminishing returns and such).
I once worked on a loan system. The original 20 year-old system was re-written in C#. The main moving bits:
Client
Loan Amount
Payment schedule
Financial transactions (interest, payments, etc.)
All-in-all it is really a simple system. Well, 800+ tables later and stacks of developers/BAs and the system is somewhat of a monster. One could even capture stock and title deeds as guarantee. Now, my take would be to scan in some of this information and link it to the loan. However, somehow some business folks decide that they absolutely "must have" this information in the system. It isn't core though, I would say.
On the other end, another system I worked on calculated premiums. It was modeled quite business-like and was quite a maintenance nightmare. It was then re-written very generically by simply defining calculations that work on given inputs. There were some lookup tables for values and so on but no business processing as such.
Sometimes we may need to abstract moving bits into something that makes sense as an input or output and then use that in our domain. I think the UL should be used by ourselves and domain experts but it doesn't mean that we are not going to end up using technical concepts that are not part of the UL, and I think that that is okay. I'm sure a domain expert wouldn't care much for a SqlDbConnection even though we are going to using one of those in our code :) --- similarly we could model some structures outside of the domain proper.
In response to your update and question: I would not create a concrete class unless it really does feature in the UL in a big way. On a side note, I still favour composition over inheritance. I typically implement interfaces where necessary and go with abstract classes when inheriting, just to place some default behaviour when it helps.
The UL, as with any design, represents a model with nuances. We can apply DDD without using domain events. When we do use domain events we may even go with event sourcing. Event sourcing has very little to do with the UL in much the same way that the terms "Aggregate", "Entity", or "Value Object" would. The UL is going to be specific to the domain / domain experts and when we, as domain modelers, talk to each other we can describe various models in terms of DDD tactical patterns in order to bring across some of the specific UL concepts.
We have to listen to how a domain expert describes the problem space. As soon as we hear "When", as stated in so many other places, we know that we are probably dealing with an event. In much the same way we can listen to how a domain expert talks about the aggregates. For instance (totally bogus example):
"When a customer is registered we need to inform the supervisor of the CSR that initiated the request"
More loosely related to your example:
"When an incident takes place we need to capture some specific details regarding the incident. Depending on the type we need to capture different bits and validate that we have sufficient data to process our claim
Between these two we can see a distinct difference in how they are referring to interacting with the problem space. When a domain expert thinks of something in very broad terms I think it is prudent that we do the same.
On the other hand, should the conversation be more along the lines of this:
"When a car accident is registered we need to assign an assessor an wait for an assessment report that has to answer..."
Now we have something much more specific. These are, necessarily, mutually exclusive in that if they only ever talk about specifics then we go with "specific". If they first mention in broad terms and then specifics, we can also work in broad terms.
This is where our modeling is tricky to get right. It is the same nuance as we have in the Address as an aggregate vs value object "debate". It all depends on the context.
These things are going to be tricky and dependent on the domain in order to get right. As Eric Evans did mention: it may take a couple of models to get something that fits just right. This is necessarily so based on one's experience with the domain.
My question, is not a philosophical one, but one of methodology. I understand how we build software to mimic everyday processes and objects, like the 'car' object so well demonstrated. My question is about lesser concrete things. For example, If I were to build a search application that returns products and prices from a database (as a part of a much larger application), would I imagine this in terms of how it might be implemented in life? For example, a 'search agent' object in code that would mimic a real life 'human search agent' (create attributes and methods from that)? Essentially, if something doesn't have an obvious real-life counterpart, do we take that idea and create a representation of it so we CAN code it? How should I think about objects in an application that do not mimic life so much?
Thanks for all your input
Object Oriented design is not about mimicking real life objects.
That is just a lazy guidance on how to abstract objects for your problem domain. A good start but is not sufficient for more abstract problem domains.
The underlying idea is to be able to abstract those units that can be abstracted from other units within you problem domain based on data and behavior.
No, objects are conceptual units.
Real life objects are just used to INTRODUCE object oriented ideas, but objects don't have to correspond to "real" things, they also correspond to abstract concepts that have no real life equivalent.
Look at the functionality ,your inputs and outputs.
Look for tasks to be done for example, Retrieving the data , processing the data and creating logical tables , representation of the data.
You can break these tasks into smaller , yet similar tasks. For example the Connection to server tasks. The request sending tasks , parsing the request back. Try to break down your objective in smallest pieces and then you can put these small functions and data members into classes.
To be perfectly clear, I do not expect a solution to this problem. A big part of figuring this out is obviously solving the problem. However, I don't have a lot of experience with well architected n-tier applications and I don't want to end up with an unruly BLL.
At the moment of writing this, our business logic is largely a intermingled ball of twine. An intergalactic mess of dependencies with the same identical business logic being replicated more than once. My focus right now is to pull the business logic out of the thing we refer to as a data access layer, so that I can define well known events that can be subscribed to. I think I want to support an event driven/reactive programming model.
My hope is that there's certain attainable goals that tell me how to design these collection of classes in a manner well suited for business logic. If there are things that differentiate a good BLL from a bad BLL I'd like to hear more about them.
As a seasoned programmer but fairly modest architect I ask my fellow community members for advice.
Edit 1:
So the validation logic goes into the business objects, but that means that the business objects need to communicate validation error/logic back to the GUI. That get's me thinking of implementing business operations as objects rather than objects to provide a lot more metadata about the necessities of an operation. I'm not a big fan of code cloning.
Kind of a broad question. Separate your DB from your business logic (horrible term) with ORM tech (NHibernate perhaps?). That let's you stay in OO land mostly (obviously) and you can mostly ignore the DB side of things from an architectural point of view.
Moving on, I find Domain Driven Design (DDD) to be the most successful method for breaking a complex system into manageable chunks, and although it gets no respect I genuinely find UML - especially action and class diagrams - to be critically useful in understanding and communicating system design.
General advice: Interface everything, build your unit tests from the start, and learn to recognise and separate the reusable service components that can exist as subsystems. FWIW if there's a bunch of you working on this I'd also agree on and aggressively use stylecop from the get go :)
I have found some o fthe practices of Domain Driven Design to be excellent when it comes to splitting up complex business logic into more managable/testable chunks.
Have a look through the sample code from the following link:
http://dddpds.codeplex.com/
DDD focuses on your Domain layer or BLL if you like, I hope it helps.
We're just talking about this from an architecture standpoint, and what remains as the gist of it is "abstraction, abstraction, abstraction".
You could use EBC to design top-down and pass the interface definitions to the programmer teams. Using a methology like this (or any other visualisation technique) visualizing the dependencies prevents you from duplicating business logic anywhere in your project.
Hmm, I can tell you the technique we used for a rather large database-centered application. We had one class which managed the datalayer as you suggested which had suffix DL. We had a program which automatically generated this source file (which was quite convenient), though it also meant if we wanted to extend functionality, you needed to derive the class since upon regeneration of the source you'd overwrite it.
We had another file end with OBJ which simply defined the actual database row handled by the datalayer.
And last but not least, with a well-formed base class there was a file ending in BS (standing for business logic) as the only file not generated automatically defining event methods such as "New" and "Save" such that by calling the base, the default action was done. Therefore, any deviation from the norm could be handled in this file (including complete rewrites of default functionality if necessary).
You should create a single group of such files for each table and its children (or grandchildren) tables which derive from that master table. You'll also need a factory which contains the full names of all objects so that any object can be created via reflection. So to patch the program, you'd merely have to derive from the base functionality and update a line in the database so that the factory creates that object rather than the default.
Hope that helps, though I'll leave this a community wiki response so perhaps you can get some more feedback on this suggestion.
Have a look in this thread. May give you some thoughts.
How should my business logic interact with my data layer?
This guide from Microsoft could also be helpful.
Regarding "Edit 1" - I've encountered exactly that problem many times. I agree with you completely: there are multiple places where the same validation must occur.
The way I've resolved it in the past is to encapsulate the validation rules somehow. Metadata/XML, separate objects, whatever. Just make sure it's something that can be requested from the business objects, taken somewhere else and executed there. That way, you're writing the validation code once, and it can be executed by your business objects or UI objects, or possibly even by third-party consumers of your code.
There is one caveat: some validation rules are easy to encapsulate/transport; "last name is a required field" for example. However, some of your validation rules may be too complex and involve far too many objects to be easily encapsulated or described in metadata: "user can include that coupon only if they aren't an employee, and the order is placed on labor day weekend, and they have between 2 and 5 items of this particular type in their cart, unless they also have these other items in their cart, but only if the color is one of our 'premiere sale' colors, except blah blah blah...." - you know how business 'logic' is! ;)
In those cases, I usually just accept the fact that there will be some additional validation done only at the business layer, and ensure there's a way for those errors to be propagated back to the UI layer when they occur (you're going to need that communication channel anyway, to report back persistence-layer errors anyway).
I'm a student currently dabbling in a .Net n-tier app that uses Nhibernate+WCF+WPF.
One of the things that is done quite terribly is object graph serialisation, In fact it isn't done at all, currently associations are ignored and we are using DTOs everywhere.
As far as I can tell one method to proceed is to predefine which objects and collections should be loaded and serialised to go across the wire, thus being able to present some associations to the client, however this seems limited, inflexible and inconsistent (can you tell that I don't like this idea).
One option that occurred to me was to simply replace the NHProxies that lazy load collection on the client tier with a "disconnectedProxy" that would retrieve the associated stuff over the wire. This would mean that we'd have to expand our web service signature a little and do some hackery on our generated proxies but this seemed like a good T4/other code gen experiment.
As far as I can tell this seems to be a common stumbling block but after doing a lot of reading I haven't been able to figure out any good/generally accepted solutions. I'm looking for a bit of direction as much as any particular solution, but if there is an easy way to make the client "feel" connected please let me know.
You ask a very good question that unfortunately does not have a very clean answer. Even if you were able to get lazy loading to work over WCF (which we were able to do) you still would have issues using the proxy interceptor. Trust me on this one, you want POCO objects on the client tier!
What you really need to consider...what has been conceived as the industry standard approach to this problem from the research I have seen, is called persistence vs. usage or persistence ignorance. In other words, your object model and mappings represent your persistence domain but it does not match your ideal usage scenarios. You don't want to bring the whole database down to the client just to display a couple properties right??
It seems like such a simple problem but the solution is either very simple, or very complex. On one hand you can design your entities around your usage scenarios but then you end up with proliferation of your object domain making it difficult to maintain. On the other, you still want the rich object model relationships in order to write granular business logic.
To simplify this problem let’s examine the two main gaps we need to fill…between the database and the database/service layer and the service to client gap. NHibernate fills the first one just fine by providing an ORM to load data into your objects. It does a decent job, but in order to achieve great performance it needs to be tweaked using custom loading strategies. I digress…
The second gap, between the server and client, is where things get dicey. To simplify, imagine if you did not send any mapped entities over the wire to the client? Try creating a mechanism that exchanges business entities into DTO objects and likewise DTO objects into business entities. That way your client deals with only DTOs (POCO of course), and your business logic can maintain its rich structure. This allows you to leverage not only NHibernate’s lazy loading mechanism, but other benefits from the session such as L1 cache.
For brevity and intellectual property reasons I will not go into the design of said mechanism, but hopefully this is enough information to point you in the right direction. If you don’t care about performance or latency at all…just turn lazy loading off all together and work through the serialization issues.
It has been a while for me but the injection/disconnected proxies may not be as bad as it sounds. Since you are a student I am going to assume you have some time and want to muck around a bit.
If you want to inject your own custom serialization/deserialization logic you can use IDataContractSurrogate which can be applied using DataContractSerializerOperationBehavior. I have only done a few basic things with this but it may be worth looking into. By adding some fun logic (read: potentially hackish) at this layer you might be able to make it more connected.
Here is an MSDN post about someone who came to the same realization, DynamicProxy used by NHibernate makes it not possible to directly serialize NHibernate objects doing lazy loading.
If you are really determined to transport the object graph across the network and preserve lazy loading functionality. Take a look at some code I produced over here http://slagd.com/?page_id=6 . Basically it creates a fake session on the other side of the wire and allows the nhibernate proxies to retain their functionality. Not saying it's the right way to do things, but it might give you some ideas.