When implementing a domain model, often object-relational mapping technologies are used. Like many tools, with their use comes the danger of abuse – abuse to the point of invalidating the benefits of the pattern itself.

From some pointers about how to use (and not to use) these tools, see why object-relational mapping sucks.

Martin Fowler’s has this to say about the Domain Model Pattern:

At its worst business logic can be very complex. Rules and logic describe many different cases and slants of behavior, and it’s this complexity that objects were designed to work with. A Domain Model creates a web of interconnected objects, where each object represents some meaningful individual, whether as large as a corporation or as small as a single line on an order form.

In short, using Object-Oriented techniques to handle the complexity.

A more comprehensive discussion about what happens when it is not used can be found under the Anemic Domain Model Anti-Pattern:

The basic symptom of an Anemic Domain Model is that at first blush it looks like the real thing. There are objects, many named after the nouns in the domain space, and these objects are connected with the rich relationships and structure that true domain models have. The catch comes when you look at the behavior, and you realize that there is very little behavior on these objects. Indeed often these models come with design rules that say that you are not to put any domain logic in the the domain objects. Instead there are a set of service objects which capture all the domain logic. These services live on top of the domain model and use the domain model for data.

The fundamental horror of this anti-pattern is that it’s so contrary to the basic idea of object-oriented design; which is to combine data and process together. The anemic domain model is really just a procedural style design…

In terms of Domain-Driven Design, this pattern is also known as Domain Layer.

Domain Models do a lot for encapsulating Business Rules, thus making them amenable to automated testing. This hinges on keeping the Domain Model independent of things related to Data Access.

It is therefore almost required to use some kind of Object/Relational Mapping tool to make it possible to persist objects belonging to the domain model to databases and other kinds of storage.

The use of DataSets in .NET is often a sign of the Anemic Domain Model Anti-Pattern.

One thing to keep in mind when working on a domain model is that you probably won’t get it “right” the first time, and will have re-work the division of responsibility a couple of times. Techniques like Test-Driven Development help out immensely for that.

So, last night I was at the MVP dinner in TechEd and everything was nice. We had a nice meal, conversation was nice, weather was… nice. And then the volume started to rise, slowly at first, so as you don’t quite notice it. After a bit, you kind of stop talking and look around. And then I hear it…

<WWF announcer voice>
Are you ready… to RUMBLE !?!?
</WWF announcer voice>

It was Datasets vs. O/R mapping, a slight twist on the infamous datasets vs. custom objects debate, all over again. They pulled me in, kicking and screaming, I swear, I really do. The lines were drawn, maintainability, performance, all the things that architects like to philosophize about in terms of other people’s work.

Anyway, I won’t give you the play-by-play ‘cause we were there almost all night. I’ll just cut to the chase.

First things first – any comparison of solutions without the context of a problem leads nowhere, fast, and stays there. So the first question I asked (when I got the chance to speak) was “are we talking about querying/reporting here?” and the answer was something like “well, yeah, but a lot of other things too”. So my suggestion was that we discuss the solutions in terms of two contexts – querying/reporting and OLTP.

What I mean by OLTP is the data-updating kind of work that you do on certain items. Examples of this include “insert order”, “change customer address”, and “discount product”. Querying/reporting doesn’t change data, and often involves dealing with large sets of data pulled from different kinds of entities (in ERD terms).

Luckily, my suggestion to deal with them separately was accepted. Secondly, I proposed that an object model (specifically implementing the Domain Model pattern) designed for OLTP would perform poorly when used for querying/reporting – simply because it wasn’t designed for it. The structure of a domain model is such that it makes it possible to define / implement business rules in one place. That’s possible, not easy.

Well, the dataset people weren’t going to just hand me the OLTP side of the equation without a fight, so they mentioned how easy it was to just “AcceptChanges”, and that my way was much more complex. My rebuttal came in the form of a question (are you seeing a pattern here?): Do you just swallow DbConcurrencyExceptions are do you throw all the user’s changes away when it happens? I didn’t quite make out the answer since there was a lot of mumbling going on, but I’m pretty sure they had one. I mean, you can’t develop multi-user systems using datasets without running into this situation.

The example that clinched OLTP was this. Two users perform a change to the same entity at the same time – one updates the customer’s marital status, the other changes their address. At the business level, there is no concurrency problem here. Both changes should go through. When using datasets, and those changes are bundled up with a bunch of other changes, and the whole snapshot is sent together from each user, you get a DbConcurrencyException. Like I said, I’m sure there’s a solution to it, I just haven’t heard it yet.

Now, here’s where things get interesting. I didn’t say that using a domain model automatically solves this problem. Rather, I described how each client could send a specific message, one a ChangeMaritalStatusMessage, the other a ChangeAddressMessage, to the server – in essence, giving the server the context in which each bit of data is relevant. The server could just open a transaction, get the customer object based on its Id, call a method on the customer (ChangeMaritalStatus or ChangeAddress), and commit the transaction. If two of these messages got to the server at the same time, the transactions would just cause them to be performed serially, and both transactions would succeed. The important part here is not losing the context of the changes.

When we talked about querying/reporting, things seemed quite a bit clearer. Datasets, or rather datatables seemed like a fine solution – most 3rd party controls support them out of the box. One guy mentioned that datasets performed poorly for large sets of data and that by designing custom entities for the result set, he could improve performance and memory utilization by, like, 70%. To tell you the truth, I think that if you need the performance, do it, if not, just use datasets. There isn’t much of an issue of correctness.

Just as an ending comment, in response to something someone said about scalability, I asked if they were reporting against the live OLTP data. The response was “yes”. Well, there’s a database scalability problem if I ever saw one. OLTP works most correctly when employing transactions that have an isolation level of serializable. The problem with them is that they lock up the whole table, or get blocked when a table scan is going on. Querying often results in a table scan. You can see the problem. Anyway, a common solution to this problem is to just reduce the isolation level, a quick fix that improves performance almost immediately. You take one hit in that your reports may be showing incorrect data, especially if they do aggregate type work. You might take another hit if your OLTP transactions need to do aggregate type work themselves. That second hit is pretty much unacceptable. A different solution is to accept the fact that the heaviest querying can usually show data that isn’t up to date up to the second.

In such a solution, you would have another database for reporting. It wouldn’t be just a replica of the OLTP database, but rather a lot more denormalized – which is a really not nice way of saying designed for reporting. You could then move the data from your OLTP database to the reporting database in some way (more to come on this topic) and you increase the scalability of your database. Just to define that a bit better – your OLTP database will be able to handle more transactions per unit of time, and reports will run faster, meaning that you will both improve their latency and the number of queries that can be handled per unit of time.

Anyway, I was pretty tired after all that, but if I had to sum it up I’d say something like this: before debating solutions, define the problem, you get a lot more insight into the solutions and you get it faster. That’s just win-win all around.

Domain Driven Design (DDD), alongside its growing popularity, is experiencing some growing pains. The Domain Model pattern, documented in the Patterns of Enterprise Application Architecture book, is at the heart of DDD yet the division of responsibility between it and other DDD patterns like Service Layer isn’t quite clear. To make matters worse, the value of the Domain Model pattern relative to simpler code-generation techniques remains vague. The one thing that has reached a wide consensus is that it requires a higher level of skill to employ these techniques than continue using the widespread procedural programming practices. There is one overwhelming reason to do it anyway, though, and that is that it is the cheapest way to get a system up and running right. The reasoning behind this has to do with business rules.

An exceedingly large number of systems are being built and modified today in order to support business rules. Beyond just computerizing the management of data in the enterprise, today’s systems are required to computerize the business processes that use that data, and these processes are built upon business rules.

A rule is composed of two main elements, a clause and an action. The clause defines under what circumstances the action is to be activated. An example of a rule employed in the business environment might be “if the customer is a preferred customer, then give them a 5% discount on all orders”. The rich behavior of an enterprise is governed by these interacting rules. Consider the result of adding another business rule like “if the customer has ordered $100,000 or more in the last year, then they are to be considered a preferred customer”. If a customer is not preferred, but then sends in a new order that puts them over the limit, how is the system to behave? Conversely, what if a preferred customer cancels an order bringing them under the limit?

I’ve seen too many projects that have been tasked with implementing these kinds of behaviors yet were unable to get the system running right. Customers that should have gotten discounts didn’t in some cases, and those that should not have enjoyed a discount did at times. After much time was spent trying to track down what part of the code was wrong, changing some code, testing, over and over again, an executive decision was made to put the system into production as is. The harm to the business was deemed cheaper in this case then not putting the system in production. Is it any wonder that business is skeptical of IT’s ability to handle the agile enterprise of the future where, not only will the business rules be more complex, they will be changing all the time.

The Domain Model pattern encapsulates these business rules in such a way that they will be run even when not directly invoked. This is especially critical when one rule triggers another. Intelligent use of OO principles when designing the domain can help you altogether avoid the jump in complexity found in Business Rules Engines.

Finally, we need to understand that supporting techniques like Object/Relational (O/R) mapping are but a means, and not the end. The discussions around DDD often get mired down in the relative costs of O/R mapping and procedural code generation. Persistence is a solved problem, a technical problem that has no meaning to business. Is it not time to raise the discussion to the level of business? If the only problem you are trying to solve is the manipulation of data in a database, then don’t bother with DDD and its descendents. It won’t make your life any easier. If, on the other hand, business has gotten sick of IT deciding for them how to run their business; if you are the one tasked with building the right system, you just won’t be able to do it unless you build the system right – DDD won’t be a bother, but a necessity.

After reading this article you just might be thinking that business rules management systems (BRMS’s) are the key to what SOA was supposed to bring (now that we’re in the trough of disillusionment) – that is, if you haven’t tried working with these beasts before.

There are several now-well-known fallacies around BRMS’s. One is that business analysts write the business rules, in plain English, and these rules do not require a programmer to enter/code them into the system; the BRMS handles all that.

“Costly, time-consuming transformation from business terms to programmer requirements and subsequent implementation can be reduced or eliminated. This in turn empowers business analysts to create and maintain the business logic directly, allowing them to make changes with little or no IT intervention.”

But, the author forgets to mention who performs these trivial activities:

“After testing and validation the business logic can be deployed to a business rules server.”

This brings me to the single most important thing anyone should know about the business rules approach. Employing a rules engine opens up the possibility that the system will behave non-deterministically. Consider that only 3 non-linear equations are needed to create chaotic behavior, and try to imagine what will happen in a system with hundreds and thousands of business rules that affect each other.

Yes, business rules often end up changing data which, in turn, causes other business rules to be activated. No, it is not humanly possible to look at such a set of rules and predict what will happen when a certain event occurs. You can fire such an event in a test environment and see what will happen. When the results aren’t what you wanted (that would be all the time), you can use the BRMS’s to show you which rules were run as a result of that event. Let’s see a business analyst debug that. “Plain English” my butt.

Let’s not go too much further on the BRMS on its own, but rather view it in the light of service-oriented architectures.

In the article, an approach is shown that is supposed to bring you the best of both SOA and the Business Rules Philosophy. I’m afraid that my experience has been otherwise. The author states:

“The business rules server may be implemented as a Web Service that is accessible to many SOA enabled applications across the organization. By supporting shared business logic within the SOA architecture that can be addressed by many disparate applications, organizations can reduce redundancy, speed implementation, lessen inconsistency and improve the overall efficiency of both the applications and the business processes they serve.”

This desire to concentrate all business logic into a single BRMS embodies the 11th fallacy of enterprise computing, as put forth by James Gosling “Business logic can and should be centralized”. Not to mention that this goes against the grain of SOA where each service is autonomous and is entirely responsible for all of its data and behavior. There’s another reason why the business rules community is pro centralization – the BRMS’s are so damned expensive.

Anyway, I don’t want to be all doom and gloom today so I’ll end on a positive note. While good OO practices and the use of the Domain Model Pattern will take you VERY far in making business rules explicit, and, therefore, their maintenance and evolution much less costly, sometimes you really neeed a BRMS. Just so you know, the investment you made in the domain model is not written off when you “upsize” to business rules – the rules themselves are written using the concepts exposed in the domain. As for the service, well, its message handlers keep on working the same as they always did; parsing messages and making calls on the domain model. The business rules will just respond to the events raised by the domain; message handlers don’t need to call into the BRMS.

Oh, and the next time somebody tells you how business analysts will be doing the work instead of programmers, ask them if they’re willing to take the debugging too 🙂

I had this discussion with Clemens when he was last here in Israel – his position, as was so eloquently stated here, was against, while I was pro. The question he raised “To map, or not to map?” he himself answered, “to map”. The question remaining was how to map; write the sql yourself, or let some tool write/generate it for you.

The overarching question is: what do you REALLY gain by O/R mapping?

(As an aside, among the comments of his post are those using the acronym ORM. Please stop – that acronym is already taken by Object Role Modeling.)

I’ve been using O/R mapping techniques on mission critical projects for some time now, and if I wanted to compare it to what I did before, it would not be to writing all the sql by hand. I don’t remember ever doing that – there was always code generation involved. Because, let’s face it – there’s a lot of drudgery involved for things that aren’t performance critical. No reason to do THAT by hand.

So, for me, the ONE THING that O/R mapping gives me better than what I did before is this:

O/R mapping gets me better object-oriented business logic.

That’s it.

Like Clemens said, if you “don’t know SQL and RDBMS technology in any reasonable depth”, don’t expect to get good performance. Obviously this is true for any technique. But I guess that empirically speaking, the percentage of people without said knowledge is larger in the group where you don’t HAVE to write sql.

So, I’ll bet you’re asking yourself, “if that’s all Udi gets from O/R mapping, why does he keep doing it?” Or maybe you’re asking yourself “should I get a beer? This is getting long…”

The fact of the matter is that I don’t know a better way to write business logic than by using OO techniques. I grant that data is important, but the reason that many applications are built is business logic – there’s something that this new system can/should do, that the old systems couldn’t (often using the same data).

If I could sum up my understanding of Clemens position, it would be this:

A lot of developers probably aren’t experienced, or knowledgeable enough the use O/R mapping well. Therefore writing the sql yourself is better.

While I agree with the first statement, and I think that the same could be said about communication, threading, .net and many other things, I don’t think that the conclusion logically follows.

So, I guess I would sum up my position like this:

If you would like to develop a persistent domain model, O/R mapping techniques will probably help you. If you would like your solution to perform well, you should probably learn how databases work, as well as what the O/R mapping tool does under the covers.

Ronan Bradley of www.WebServices.org predicts the failure of SOA solutions based on “coded frameworks”. To say I disagree would be an understatement. There is one section in particular that disturbs me:

“My aversion to code is not based an abstract principle. Rather, each line of code the organization develops is custom for that organization and (unfortunately) sometimes for that project. As a consequence it must be maintained and evolved over time. Furthermore, the knowledge about what that code does must be maintained in the organization and evolved over time. This is a potentially huge cost and distraction for IT organizations, which need to focus on solving business problems rather than maintaining integration code.”

1. Custom code is not necessarily integration code.
2. Some business problems are about getting access to legacy data stuck in some proprietary format.
3. IT maintains and develops code. That’s why it exists.

I worry that people will start thinking of SOA as “buy product from vendor, drag and drop, done”. Developers will always be writing code.

Let’s go back to the pipe-dreams of business-rule systems. You know, those hyper-flexible monstrosities that end-users (of all people) would define the rules.

Why don’t we, as an industry, JUST GET OVER IT.

There will always be code, as in custom code. Code without a solid design is a maintainence nightmare. Design without architecture is the right solution to the wrong problem. Architecture without requirements is answering the right question asked by the wrong person.

Nothing has changed.

Developing software will continue to be hard.

And no matter how many three letter acronyms you throw at it, software development will continue to be hard. If you don’t look at the whole lifecycle, you’re bound to optimize the small, and ruin the large.

Are we done with the hype yet?

Can we all just get back to work?

I’ve been reading a lot from the agile management blog lately, and I came upon this entry about implementing business rules with aspects. If you haven’t yet read this previous entry about the division of the system architecture not only along system lines, but also along “risk of change” lines, then I suggest you read it first.

First of all, I would like both developers and managers to read the previous entry because of its profound meaning. We CAN and should separate different parts of the system having differing levels of risk. Once again, “3-tier architectures” don’t address these issues. So, if we are dividing the architecture along risk lines as well, then obviously the UI would be the riskiest – having the highest probability to change – over the life of the project.

However, business rules are often considered quite stable. Why ? Because their time-line of change is often stretched out over many project life-times – rather obvious really, business rules deal with the business, not the project. During development of the project we are often given the requirements in such a way that it is difficult to know what is domain knowledge and what is a business rule. It takes effort to separate out what are the business rules – what has changed in the past, and what will change in the future.

For example, in an academic project I performed some time ago, I was given a set of requirements including: 1. A student can register to a given course once in a semester. 2. A student can register to a project in a semester. Which is the business rule, which is the domain ? In this case (1) is the domain, and (2) is the rule – “a project” meaning “only one project” as I later found out. This rule changed sometime after my second alpha to “A student can register to only one project alone in a semester, but several projects in the same semester as long as they have a partner for each of those projects.”

As it is apparent, I, as a developer, have to take into account these risk/change factors and change my architecture accordingly. Ever since that project I have always created a business rules layer separate from the infamous “BL” ( Business Logic ).

Now, getting to the issue of implemeting using aspects. I am a big proponent of AOP, however I often find alternative implementations to be more desirable. Most of the examples given for the use of AOP including logging, transactions, security and others that can be made part of a framework, as .Net has done in many cases. Many have pushed Java’s superiority because of AspectJ, and although .Net doesn’t have an Aspect.Net yet ( although various developments are under way ), I have yet to miss it. Clemens Vasters has done some truly incredible stuff in the use of attributes in .Net for implementing AOP stuff. I’ve always thought that attributes should be used that way. I find that there is one basic flaw in the conclusion to using aspects for connecting business rules to systems. The entire white paper is here. ( Yes, its a pdf unfortunately – only good for print really, Jakob Nielsen thinks so too. ) The basic premise is that I’m building an entire system in an OO manner, which I’ve stopped doing some time ago for these reasons. Clemens has great insights on this as well, see them here.

When using an SOA, your UI, or any other system needing services for that matter, will be sending messages to the guts of your system – the “BL” for you hardcore 3-tier-guys. Let’s call the thing receiving messages in this case the Gateway. All the gateway does is receive messages ( like “Register student number 12 to course number 15 in semester 21” ) and pass them on to the appropriate handler. The word “handler” hear is used like in the term “event handler” for a reason: The receipt of a message is an event. In the white-paper the authors refer to these events as a problem that has to be dealt with. Why ? Because when working in an object oriented fashion, you would have to intercept the call to: new Student(12).RegisterToProject(93); in order to handle the event, ie check/activate a business rule. Aspects are great for this sort of thing. However, when working in a service-oriented fashion, you would send a message of type “RegisterStudentToProject” with the parameters StudentID and ProjectID as above. No need to intercept any call since it has to first go through the gateway. The gateway would then pass the message to the business rules engine which would then find and activate the appropriate rules before and after the actual call to register the student.

The rules engine does something like this:

If ( ActivateBusinessRulesForMessageAndReturnTrueIfCanMakeCall(myMessage) )
{
MakeCallForMessage(myMessage);
ActivateBusinessRulesAfterMessage(myMessage);
}

The business rules themeselves are implemented in a separate layer than the engine. The mapping between rules and messages is also done in a layer separate from both the engine and the rules. Once we have a layer for each of these, we have architecturally separated the parts that change more often in the system from the rest of it. One can also move to a more dynamic model. One in which you define a language for defining rules, and the mapping to messages as well. Thus, changes could be made by changing a configuration file instead of recompiling any part of the system.

Note that when you have lots of rules and the order for activating them matters, you should move to a commercial rule engine instead of implementing your own. You’ll see that performance becomes an issue as the number of rules increases.

I hope that I’ve managed to introduce yet another strength of the SOA over the pure OO paradigm. Tell me what you think ! Where does the SOA fall short ? Where does the OOA beat the SOA ? Am I full of it ?