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CHAPTER 11 AUTOMATED INTEGRATION TESTING
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Figure 11 3. A na ve view of remote systems testing
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Figure 11 4. The reality of remote systems testing The same problems that take place between code interfaces during unit or controller testing become much bigger, and a whole new breed of problems is also introduced. Here are some of the typical issues that you may well encounter when writing remote integration tests in a shared environment:
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CHAPTER 11 AUTOMATED INTEGRATION TESTING
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Network latency Data contention (where two or more remote systems may be competing to read or update the same data simultaneously) Database metadata changes Randomly Mutating Interfaces Bugs in the remote system Security firewalls, secure sessions, expired keys, etc. Cloudy days
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We ve been looking at some of these issues in the course of this chapter, presenting ways to mitigate each one. Let s have a quick run-through of the remaining issues here.
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Note We hope that, by the end of the chapter, you ll agree with us that the problems we ve just described aren t just limited to integration tests they re typical of systems development in general, and integration tests actually highlight these problems earlier, saving you time overall.
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Network Latency
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Socket code that works perfectly on one PC with local loopback might fail unexpectedly when connecting over a network, simply because communication takes longer. The programmer might not have thought to include a retry function, because the code never timed out while running it locally. Similarly, he may not have included buffering, simply reading data until no more bytes are available (when more could still be on the way), because locally the data would always all arrive at once. This is a good example of where struggling to create an integration test (and the test environment, with network-deployed middleware, etc.) can actually save time in the long run. Encountering these real issues in an end-to-end test means they ll be addressed during development, rather than later when the allegedly finished system is deployed, and discovered not to be working.
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Database Metadata Changes
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We touched on this in the previous section, but the problem of a database changing (tables being dropped or renamed, new columns added/renamed/removed, or their type being changed, foreign keys randomly removed, and so on) seems to have a particularly harsh effect on automated tests. Each time the database is changed, it s not just the product code that needs to be updated, but the tests that assume the previous structure as well. Keeping your tests black box can help a lot here. In fact, as you ll see later, the only real way for integration tests to be viable is to keep them as black box as possible. Because their scope is much broader than myopic unit tests, they re susceptible to more changes at each juncture in the system they pass over. So the fewer assumptions about the system under test that are placed in the test code, the more resilient your integration tests will be to changes. In the case of database changes, this means not putting any knowledge of the database at all (column names, table names, etc.) in the tests, but making sure everything goes through a business domain-level interface.
CHAPTER 11 AUTOMATED INTEGRATION TESTING
Randomly Mutating (aka Agile ) Interfaces
Evolutionary development (as agile used to be known) has become rather popular, because it gives teams the excuse to design the system as they go along, refactoring services, interfaces, and data structures on the way.14 While the opposite antipattern (the rigid refusal to change anything once done) is also bad, being too fluid or agile can be highly problematic in a multi-team project. Team A publishes an interface that is consumed by team B s client module. Then team A suddenly changes their interface, breaking team B s module because team B had somehow forgotten that other teams were using their public interface. It happens all the time, and it slows development to a crawl because teams only find out that their (previously working) system has broken at the most inopportune moments. Again, this will break an automated test before it breaks the real deployed product code. This may be regarded as an example of why automated integration tests are so fragile, but, in fact, it s another example of the automated tests providing an early warning that the real system will break if it s deployed in its current state.
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