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NOV
20
2015

Testing With Data

It's not a coincidence that this is coming off the heels of Dave Paquette's post on GenFu and Simon Timms' post on source control for databases in the same way it was probably not a coincidence that Hollywood released three body-swapping movies in the 1987-1988 period (four if you include Big).

I was asked recently for some advice on generating data for use with integration and UI tests. I already have some ideas but asked the rest of the Western Devs for some elucidation. My tl;dr version is the same as what I mentioned in our discussion on UI testing: it's hard. But manageable. Probably.

The solution needs to balance a few factors:

  • Each test must start from a predictable state
  • Creating that predictable state should be fast as possible
  • Developers should be able to figure out what is going on by reading the test

The two options we discussed both assume the first factor to be immutable. That means you either clean up after yourself when the test is finished or you wipe out the database and start from scratch with each test. Cleaning up after yourself might be faster but has more moving parts. Cleaning up might mean different things depending on which step you're in if the test fails.

So given that we will likely re-create the database from scratch before each and every test, there are two options. My current favourite solution is a hybrid of the two.

Maintain a database of known data

In this option, you have a pre-configured database. Maybe it's a SQL Server .bak file that you restore before each test. Maybe it's a GenerateDatabase method that you execute. I've done the latter on a Google App Engine project, and it works reasonably well from an implementation perspective. We had a class for each domain aggregate and used dependency injection. So adding a new test customer to accommodate a new scenario was fairly simple. There are a number of other ways you can do it, some of which Simon touched on in his post.

We also had it set up so that we could create only the customer we needed for that particular test if we needed to. That way, we could use a step like Given I'm logged into 'Christmas Town' and it would set up only that data.

There are some drawbacks to this approach. You still need to create a new class for a new customer if you need to do something out of the ordinary. And if you need to do something only slightly out of the ordinary, there's a strong tendency to use an existing customer and tweak its data ever so slightly to fit your test's needs, other tests be damned. With these tests falling firmly in the long-running category, you don't always find out the effects of this until much later.

Another drawback: it's not obvious in the test exactly what data you need for that specific test. You can accommodate this somewhat just with a naming convention. For example, Given I'm logged into a company from India, if you're testing how the app works with rupees. But that's not always practical. Which leads us to the second option.

Create an API to set up the data the way you want

Here, your API contains steps to fully configure your database exactly the way you want. For example:

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Given I have a company named "Christmas Town" owned by "Jack Skellington"
And I have 5 product categories
And I have 30 products
And I have a customer
...

You can probably see the major drawback already. This can become very verbose. But on the other hand, you have the advantage of seeing exactly what data is included which is helpful when debugging. If your test data is wrong, you don't need to go mucking about in your source code to fix it. Just update the test and you're done.

Also note the lack of specifics in the steps. Whenever possible, I like to be very vague when setting up my test data. If you have a good framework for generating test data, this isn't hard to do. And it helps uncover issues you may not account for using hard-coded data (as anyone named D'Arcy O'Toole can probably tell you).


Loading up your data with a granular API isn't realistic which is why I like the hybrid solution. By default, you pre-load your database with some common data, like lookup tables with lists of countries, currencies, product categories, etc. Stuff that needs to be in place for the majority of your tests.

After that, your API doesn't need to be that granular. You can use something like Given I have a basic company which will create the company, add an owner and maybe some products and use that to test the process for creating an order. Under the hood, it will probably use the specific steps.

One reason I like this approach: it hides only the details you don't care about. When you say Given I have a basic company and I change the name to "Rick's Place", that tells me, "I don't care how the company is set up but the company name is important". Very useful to help narrow the focus of the test when you're reading it.

This approach will understandably lead to a whole bunch of different methods for creating data of various sizes and coarseness. And for that you'll need to...

Maintain test data

Regardless of your method, maintaining your test data will require constant vigilance. In my experience, there is a tremendous urge to take shortcuts when it comes to test data. You'll re-use a test company that doesn't quite fit your scenario. You'll alter your test to fit the data rather than the other way around. You'll duplicate a data setup step because your API isn't discoverable.

Make no mistake, maintaining test data is work. It should be treated with the same respect and care as the rest of your code. Possibly more so since the underlying code (in whatever form it takes) technically won't be tested. Shortcuts and bad practices should not be tolerated and let go because "it's just test data". Fight the urge to let things slide. Call it out as soon as you see it. Refactor mercilessly once you see opportunities to do so.

Don't be afraid to flip over a table or two to get your point across.

-- Kyle the Unmaintainable


Kyle Baley

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