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It s to be expected that the remote system is under construction just as your client system is. So the team developing the other system is bound to have their fair share of teething troubles and minor meltdowns. A set of automated integration tests will find a problem straightaway, causing the tests to break when, otherwise, the other team may have quietly fixed the problem before anyone even noticed. So automated tests can amplify integration issues, forcing teams to address a disproportionately higher number of problems. This can be viewed as a good or a bad thing depending on how full or empty your cup happens to be on that day. On the positive side, bugs will probably be fixed a lot quicker if they re discovered and raised much sooner i.e., as soon as one of your tests breaks.
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Cloudy Days
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A cloudy day isn t a tangible problem in fact, perhaps we re just feeling a bit negative after listing all these other problems! But there are definitely days when nothing on an agile project seems to fit together quite right you know, those days when the emergent architecture emerges into a Dali-like dreamscape. Whole days can be wasted trying to get client module A to connect with and talk to middleware module B, Figure 11 5 being a case in point! If client module A happens to be test code, it s tempting to give up, deeming the test effort not worth it, and return to the product code storing up the integration issues for later. With these problems in mind, it could be easy to dismiss integration tests as just too difficult to be worth bothering with. But that would be to miss their point and their intrinsic value entirely.
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Our favorite example of this is Scott Ambler s epic work on Agile Database Techniques (Wiley, October 2003) much beloved by DBAs everywhere. And our favorite line: Therefore if data professionals wish to remain relevant they must embrace evolutionary development. Riiiiight
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CHAPTER 11 AUTOMATED INTEGRATION TESTING
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Figure 11 5. When it comes to integration, even the best software can have a cloudy day.
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1. Don t Underestimate the Value of Integration Tests
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Integrating two systems is one of the most problematic areas of software development. Because it s so difficult, automated integration tests are also difficult to write and maintain not least because they keep breaking, for exactly the same reasons remote code keeps breaking. So many teams simply avoid writing integration tests, pointing out their problematic nature as the reason. Kind of ironic, huh As we demonstrated earlier in this chapter with the Hotel Search controller-level test, the real value of integration tests is in providing a consistent, relentless checking of how your code matches up with live, external interfaces. External interfaces are, by their nature, outside your team s control; so there s value in an ever-present breaker switch that trips whenever an interface has been updated with a change that breaks your code. A breaking integration test also immediately pinpoints the cause of a problem. Otherwise, the error might manifest with a seemingly unrelated front-end error or oddity a strange message or garbled data appearing in your web application which would take time to trace back to some random change made by one of your service vendors, or by another team that you re working with. The integration test, conversely, will break precisely because the external interface has done something unexpected.
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Key Points When Writing Integration Tests
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We ll round off the chapter by summing up some of the key points (and adding a couple of new ones) to think about while writing integration tests. Here is our list: Create a test environment (test database, etc.) to run the tests in. This should be as close as possible to the live release environment. A frequent data refresh from the live system will keep the test database fresh and realistic. Multiple test environments may be necessary, but try not to go crazy as they all need to be maintained. However, you might want one database that can be torn down and reinstated regularly to provide a clean environment every time, plus a database with a dataset similar to the live system, to allow system, load, and performance testing. Start each test scenario with a script that creates a test sandbox containing just the data needed for that test. A common reason given for not running integration tests against a real database is that it would take too much effort to reset the database prior to each run of the test suite. In fact, it s much easier to simply have each test scenario set up just the data it needs to run the scenario.
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