Friday, January 21, 2011

Maintaining One Code Base with Possibly Conflicting Custom Features

Today's essay deals with the tricky issue of custom features for individual customers who are running instances of your software.

The question comes by way of a regular reader who prefers to remain anonymous, but asks this:

... I work on a large (to me, anyway) application that serves as a client database, ticket system, time-tracking, billing, asset-tracking system. We have some customers using their own instances of the software. Often, those customers want additional fields put in different places (e.g., a priority column on tickets). This results in having multiple branches to account for versions with slight changes in code and in the database. This makes things painful and time-consuming in the long run: applying commits from master to the other branches requires testing on every branch; same with database migrate scripts, which frequently have to be modified.

Is there an easier way? I have thought about the possibility of making things "optional" in the database, such as a column on a table, and hiding its existence in the code when it's not "enabled." This would have the benefit of a single code set and a single database schema, but I think it might lead to more dependence on the code and less on the database -- for example, it might mean constraints and keys couldn't be used in certain cases.

Restating the Question

Our reader asks, is it better to have different code branches or to try to keep a lot of potentially conflicting and optional items mixed in together?

Well, the wisdom of the ages is to maintain a single code branch, including the database schema. I tried exactly once, very early in my career, to fork my own code, and gave up almost within days. When I went to work in larger shops I always arrived in a situation where the decision had already been made to maintain a single branch. Funny thing, since most programmers cannot agree on the color of the sky when they're staring out the window, this is the only decision I have ever seen maintained with absolute unanimity no matter how many difficulties came out of it.

There is some simple arithmetic as to why this is so. If you have single feature for a customer that is giving you a headache, and you fork the code, you now have to update both code branches for every change plus regression test them both, including the feature that caused the headache. But if you keep them combined you only have the one headache feature to deal with. That's why people keep them together.

Two Steps

Making custom features work smoothly is a two-step process. The first step is arguably more difficult than the second, but the second step is absolutely crucial if you have business logic tied to the feature.

Most programmers when confronted with this situation will attempt to make various features optional. I consider this to be a mistake because it complicates code, especially when we get to step 2. By far the better solution is to make features ignorable by anybody who does not want them.

The wonderful thing about ingorable features is they tend to eliminate the problems with apparently conflicting features. If you can rig the features so anybody can use either or both, you've eliminated the conflict.

Step 1: The Schema

As mentioned above, the first step is arguably more difficult than the second, because it may involve casting requirements differently than they are presented.

For example, our reader asks about a priority column on tickets, asked for by only one customer. This may seem like a conflict because nobody else wants it, but we can dissolve the conflict when we make the feature ignorable. The first step involves doing this at the database or schema level.

But first we should mention that the UI is easy, we might have a control panel where we can make fields invisible. Or maybe our users just ignore the fields they are not interested in. Either way works.

The problem is in the database. If the values for priority come from a lookup table, which they should, then we have a foreign key, and we have a problem if we try to ignore it:

  • We can allow nulls in the foreign key, which is fine for the people ignoring it, but
  • This means the people who require it can end up with tickets that have no priority because it does not prevent a user from leaving it blank.

A simple answer here is to pre-populate your priority lookup table with a value of "Not applicable", perhaps with a hardcoded id of zero. Then we set the default value for the TICKET.priority to zero. This means people can safely ignore it because it will always be valid.

Then, for the customer who paid for it, we just go in after the install and delete the default entry. It's a one-time operation, not even worth writing a script for, and it forces them to create a set of priorities before using the system. Further, by leaving the default of zero in there, it forces valid answers because users will be dinged with an FK violation if they do not provide a real priority.

For this particular example, there is no step 2, because the problem is completely solved at the schema level. To see how to work with step 2, I will make up an example of my own.

Step 2: Unconditional Business Logic

To illustrate step 2, I'm going to make up an example that is not really appropriate to our reader's question, frankly because I cannot think of one for that situation.

Let's say we have an eCommerce system, and one of our sites wants customer-level discounts based on customer groups, while another wants discounts based on volume of order -- the more you buy, the deeper the discount. At this point most programmers start shouting in the meeting, "We'll make them optional!" Big mistake, because it makes for lots of work. Instead we will make them ignorable.

Step 1 is to make ignorable features in the schema. Our common code base contains a table of customer groups with a discount percent, and in the customers table we make a nullable foreign key to the customer groups table. If anybody wants to use it, great, and if they want to ignore it, that's also fine. We do the same thing with a table of discount amounts, we make an empty table that lists threshhold amounts and discount percents. If anybody wants to use it they fill it in, everybody else leaves it blank.

Now for the business logic, the calculations of these two discounts. The crucial idea here is not to make up conditional logic that tries to figure out whether or not to apply the discounts. It is vastly easier to always apply both discounts, with the discounts coming out zero for those users who have ignored the features.

So for the customer discount, if the customer's entry for customer group is null, it will not match to any discount, and you treat this as zero. Same for the sale amount discount, the lookup to see which sale amount they qualify doesn't find anything because the table is empty, so it treats it as zero.

So the real trick at the business logic level is not to figure out which feature to use, which leads to complicatec conditionals that always end up conflicting with each other, but to always use all features and code them so they have no effect when they are being ignored.

Conclusion

Once upon a time almost everybody coding for a living dealt with these situations -- we all wrote code that was going to ship off to live at our customer's site. Nowadays this is less common, but for those of us dealing with it it is a big deal.

The wisdom of the ages is to maintain a common code base. The method suggested here takes that idea to its most complete implementation, a totally common code base in which all features are active all of the time, with no conditionals or optional features (except perhaps in the UI and on printed reports), and with schema and business logic set up so that features that are being ignored simply have no effect on the user.

86 comments:

JulesLt said...

Of course, one has to be careful that new features do have zero effect when being ignored. The repeated pattern I've encountered over the years is 'why has this batch process gone up by 25%' - and it turns out to be because it's doing a simple query that does nothing . . . 500,000 times.

(Back to the problems of encapsulation vs optimising loops).

Also, when it comes to UI design, my preference is for either leaving the field there (to be ignored) or greyed out if disabled. Actual invisibility either leaves odd gaps in a layout, or some kind of inevitably inferior auto-layout.

(The big exception is columns in a data grid)

JulesLt said...

Should add that the 'do nothing 500,000 times' example isn't a DBMS problem. The query itself could take 0 msecs, it's the 500,000 IPC or network calls that are the problem!

zippy1981 said...

Ken, I gotta say I like your solution enough to try it out next time I'm on that situation.

I do have two comments though regarding the two alternatives.

I think maintaining separate branches is becoming easier with modern SCM tools and dev practices. At the very least, good merge tools, continuous integration, and good unit test coverage (in terms of meaningful coverage, not just running through all your branches) make the process more mechanical.

With regards to custom db deploy scripts, who writes deploy scripts manually anymore? On the Microsoft side of things, higher end versions of Visual Studio, or Redgate SQL compare will let you merge schemas.

Yes, sometimes you have to edit the script, especially if there is a need to do some DML, I personally find that to be rare in practice. I am very "write it by hand" when it comes to DDL scripts on the dev machine, but I just don't see the sense in doing subsequent deploys towards production.

Maureen Grace said...
This comment has been removed by the author.
Mika Kukkonen said...

"Code that was going to ship off to live at our customer's site" has become code that is going to live at a single-tenant SaaS app. But the principles are the same.

Vojislav Depalov said...

We are using one table which is used to switch off or switch on different functionality. Also have one code base, without branching. Maintain "regular" code, from my point of view, is different than maintain database code. There is one more variable which do not exists in "regular" code, and exists in databases. This is time. And data, as a consequence of time. It means that it is possible to get latest version of "regular" code, and deliver it, but database should be upgraded(I regard here schema and data changes). So, the same mechanism can not be applied.

John Zabroski said...

> There is some simple arithmetic as to why this is so. If you have single feature for a customer that is giving you a headache, and you fork the code, you now have to update both code branches for every change plus regression test them both, including the feature that caused the headache. But if you keep them combined you only have the one headache feature to deal with. That's why people keep them together.

I debated posting a reply to this, and took some time to mull over exactly what I wanted to say.

First, you are right. At the surface, it is simple arithmetic.

But the underlying problem of having a feature implemented two different ways for two separate clients still exists, and gets worse as the number of clients approaches infinity. Computer scientists specializing in software engineering have a name for the subfield dedicated to studying this problem: Software Factories and Software Product Lines. And these things can get very complicated. For example, ontological mapping becomes an issue. If you use the word "contract number" with the wrong client, then they will give you an insurance contract number, rather than the global insurance plan id. Or vice versa: Use the word "insurance plan" and they give you contract level details instead. It all depends on how their accounting subsystem was set-up. These sorts of ontological issues were covered in William Kent's fantastic book, Data and Reality (1977).

Now, for a more practical view:

I think if you have a multi-tenant database and many clients, and in that database you have a table(s) with sparsely populated columns representing what features each client has flipped on, then you are begging for trouble. The pricing of your software simply will not work unless it is ridiculously expensive. I may be mistaken, but this is what happens with most shrinkwrapped and semi-extensible ERP/CRM solutions like Peoplesoft, SAP, Meditech, Epic, VPM, and so on.

Anonymous said...

In your Step 1 section, you said,

Further, by leaving the default of zero in there, it forces valid answers because users will be dinged with an FK violation if they do not provide a real priority.

Are you sure you didn't mean that if you delete the default it forces them to provide a real priority? Because if you leave the default, that customer doesn't have to provide a priority, wasn't that the point of the default?

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vlc said...

The questioner says this happens 'often' so maybe they should consider refactoring the system to use an EAV db schema.

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Einhverfr said...

I have actually gone the other way to some extent, and seen the db as a platform where functionality can be added. Although I think your approach works very well in many cases, there are cases (like ERP systems) where you are essentially shipping a framework, and that framework may have a lot of features very few customers need.

In these cases, it makes sense to follow something like your advice but also modularize so you dont have to ship the whole product to everyone.

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hey ken,
i havent spoken to you in a while about programming. i was introduced to you by donald organ and tom melendez...you worked on "circuits" for me a few years back. I was wondering if you could shoot me an email when you get a quick chance. i could use a little advice as i proceed with my project..thanx john
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