Strategies for Test Databases?

youngcfan asks: "I've been tasked with finding strategies for a test database that can be used effectively by both software developers and the QA team. We're a J2EE shop with most of the interesting pieces of the application interacting heavily with the database -- so we need to test it. We're ramping up on JUnit, but are looking for ways to test the database-driven pieces of code. Since QA needs the same database for functional testing separate from developers' unit tests, DBUnit doesn't seem to suffice. We also have the challenge of working on multiple releases at the same time, which only complicates how and when to add new data to the test database in a way that's useful and valid for everyone. We're looking for strategies for using a test database in a way that meets both the QA's and the developers' needs, works for multiple releases, and isn't a heavy burden to maintain given that the schema and code can change anytime before any of the multiple upcoming releases. Any suggestions?"

Comments

Why use only one DB?

[Dr. Hok]

Why do you insist on using one DB for both developers and QA? They have different test scopes, so they should use different DBs. It's like using an axe to both chop wood and cut fingernails.

You'll find it much easier to create dedicated DBs for each test scope.

Re:Why use only one DB?

[kfg]

Ok, maybe it didn't turn out to be such a hot idea, but as side effect it is easier for me to compute in base 8 now.

KFG

Re:Why use only one DB?

[djbckr]

As the parent eludes to, the only way to do it The Right Way (tm) is to have a Development environment, a QA environment, and a Production system.

Each of these systems should be using the same architecture when it comes to hardware and configuration.

The Development system is always in a state of flux, as its name implies.

The QA system should *at least* approximate (if not be identical to) the data and load of the production system, and it should be treated like a production system that QA tries to break.

It is only in this fashion that you will be able to test and make sure your system will work as expected. Leave nothing to chance. Expensive, yes. But it's less expensive than a downed production system, and definitely less expensive than building a complete system and realising it doesn't perform as expected.

Use real data, not test data

[SMQ]

Test data sucks: there are too many real-world situations the developers fail to think of.

We're a pretty small shop, but here's what we do: The production server backup is loaded to the test server daily. Every developer maintains a set of scripts which make any needed databae structure modifications after the backup has loaded. All development and QA testing is done against this test database. Where the production data isn't stable enough for unit testing we force-feed a few specific rows (as few as possible). This gives us fresh, real-world data for development and testing, and when an application rolls out, the exact same set of modification scripts are usually run on the production server (i.e. the modification scripts have been indirectly but repeatedly tested themselves).

Doesn't Suffice?

[Aladrin]

DBUnit doesn't suffice? What's it missing? It's only function is to place the database into a known state before the test, to make sure the data is correct before you test with it. How can that not do what you want?

It also occurs to me that if you can't even decide what data is 'useful and valid to everyone' then your test data is nothing like the live data you will have. Here's my suggestion: If it seems like it'll be even slightly relevant to anyone, use it. Otherwise you aren't testing everything.

The constantly changing schema is puzzling also. Did you not plan your database beforehand? I'm guessing this is an XP shop then, eh? XP doesn't stand for 'no planning'. I can understand changes to the schema in the early stages of programming, but if you're getting close to 'multiple releases' then the schema should be pretty solid by now, and the little changes needed to make to DBUnit shouldn't be a big bother.

For test databases...

[Ramses0]

For (QA) test databases, it's generally not enough to just have a separate instance, you also need to support the following capabilities:

    1- "Clone" whatever is most recent on production

    2- Revert to "known good QA state" (ie: big red reset button)

    3- Dump current state for later use.

You need to be able to clone so that ad-hoc testing can be run against production data w/o making production impact. This doesn't have to be live, but can be like a once-a-week/once-a-month activity, or rotate out a slave DB every once in a while, or have your DB people test your backups / etc.

You need the ability to revert to a known good state so that specific tests can be run and those can be more easily automated. Like: search "foo", 7 results found (not 6, not 8, not "it was 8 a few seconds ago but now it's 9 because there's a new result that was just added) ... the more confident QA is in the data, the more confident (and/or prone-to-automation) their can be.

The ability to dump out DB state is a very distant third, but can be helpful for post-testing analysis or being able to modify a particular DB snapshot to fit some particular testing needs and then dump that out to the file-system for later use.

QA is hard, thank you for trying to make it easier.

--Robert

DB for Unit Testing?

[Slashdot Parent]

A couple of points.

1. Typically, the term Unit Testing refers to the testing of a single, fine-grained unit of code. In other words, to do your true Unit Tests, you should not be accessing any database.
2. The question that I think you are asking, is "How do I get databases initialized with the correct schema and correct data for integration testing?" The answer is, as always, "It depends."

The two biggest factors for creating useful test environments are: "How often does your schema change?", and "How much data do you need in your database for meaningful test cases?"

Schema Changes: As a J2EE architect, the first time I saw Ruby on Rails' database migrations my first impulse was to wonder, "Why the !@#$ is this not in Hibernate?" I am not aware of any slick framework for J2EE apps to manage DB migrations, so you may have to use your own migration scripts. Hopefully, your schema is not changing much.

Getting Data In There: This totally depends on how much data you need. My "favorite" reply to you was to have one snapshot of your production data per developer. That works great, as long as you don't have much data. My last project had I don't even remember how many terrabytes of data in prod. Do you really think the client was going to spring for that much storage and that many Oracle licenses to get one instance per developer? Yeah right. We had a full snapshot for performance testing, but regular integration testing was done on a representative subset of data.

DBUnit is a great way to initialize a small amount of data. For larger datasets, you cannot get away with things like DBUnit, as it would take hours, if not days, to get the data in there. For our performance testing databases, we had the prod data snapshot stored on a RAID-1. Before testing started, we broke the mirror and did testing against the degraded array. When it came time to reset the data, we shut down Oracle and rebuilt the array to the good snapshot. That wound up being very fast for us. For medium amounts of data, you could probably get away with using SQL*Loader.

DBUnit can be very useful

[mikeburke]

I work with a large, legacy codebase - about 2 million lines of code, 600 tables. Some bits are nicely written, some aren't. Concepts such as dependency injection, seperation via interfaces etc are not prevasive, so traditional unit testing approaches of mocks or HSQL are not useful (in fact I find they do not scale for 'meaningful' tests anyway).

So you have this legacy code base - you want to make changes, but how can you validate the result? One approach is to compare database states - one from a known good codebase, one from a modified codebase. DBUnit can be tremendously useful here - this is what I've done (perhaps too complex for explaining on Slashdot):

Create a common Unit Test base class that extends DBUnit's DatabaseTestCase. It will:

    a) receive a list of modified table names from the concrete test class
    b) if a system property is set, export a pristine copy of these tables prior to running the test - 'reference data'.
    c) execute the use case (register a user, perform a transaction, whatever) - this just makes a 'blind' call into the
          code proper.
    d) if a system property is set, export the modified table data ('known good results')

The idea is you run this test twice:

1) With the original codebase, with result exporting enabled to generate known good results.

2) With the codebase under test - the results generated will be compared against known good results and DBUnit will flag any differences. You can get it to ignore stuff like sequnces,dates that will differ between runs.

The reference data generated in (b) is reloaded prior to running the test second test, so you start from the same point. Each concrete test class just has to:

* figure out what tables change within the test
* provide the test code itself

Everything else is managed by DBUnit - exporting/importing datasets, comparing datasets, etc.