When code goes bad: What to watch for

Emergent Design: Pathologies uncovered

This happened several times. As he paged down through the code, sometimes for pages at a time, there would be nothing but a blank page, and then for pages at a time he would see code again.

He had been working all day, so he suspected that he may have corrupted the memory buffer of his IDE (Visual Studio, in this case). He restarted it. The same problem happened again, so he rebooted. Then he cold started. He checked out a fresh copy of the code from source-control. Same problem.

Now, he really hit the old "wall of voodoo". He figured it must be something strange, like a problem in the operating system or the installation of the IDE. He was, in fact, very close to taking a pretty drastic step and reinstalling either or both of these things.

Then he noticed how small the horizontal scroll button was at the bottom of his IDE.

The problem was actually very simple: the code was so complex, and had to do so much procedurally, that the nesting from the accumulating tabs in the code often pushed all the code off screen to the right, sometimes for pages at a time, until the conditional branching, looping, try/catches, and so forth all closed and the code drifted back to the right.

It was not good news (lots of work to do), but at least he knew it was not his machine. It was a problem with the code, and it was obviously very weakly cohesive.

Indicators of accidental or illogical coupling

Here are some examples of accidental or illogical coupling.

  • Unexpected side effects. The very thing we hope to avoid by paying attention to coupling is also a key indicator that we have not. When a change in one part of the system changes something in another part of the system, and this is surprising, unexpected, and illogical to you, then most likely there is coupling in the system that was not intended or does not make sense.
  • Hesitancy. When you find yourself hesitant or resistant to making a change to the system, sometimes this is simply your subconscious telling you that you know the system has coupling in it that is going to "get you" when you try to change it. Of course, ultimately, we are trying to eliminate this hesitancy because we want to be able to evolve systems as we go, but when we feel it, we should pay attention to our own reactions.
  • Comments. I have a love-hate relationship with comments. Too many comments are not a good thing, because they can get in your way (they make the code longer) and because they often do not get updated when the system changes. However, some comments can really help to make a system more readable and understandable. I have come to draw a distinction here. Some comments are about what the code is doing and often refer to other parts of the code in their explanation. This is an indicator of a problem. Why is the code simply not readable in the first place? Often, this is because it cannot be, as there are excessive dependencies with other parts of the system. This, of course, is a coupling problem. However, other comments are about why the code is doing what it's doing, which could reflect business or regulatory rules, and these can be difficult to make clear in the code. I like comments like these: the "why" comments as opposed to the "what" comments.
  • Large test fixtures. When we examine unit testing, this will make more sense; in short, a unit test needs to create an instance of the class it is designed to test. Sometimes, it has to create other instances too, because the class it is testing needs them to operate. The collection of instances created in a unit test is called the fixture for the test by some people (yours truly included). A good overall view of the coupling in a system can be obtained by looking at the suite of unit tests that test it, and taking an average of the number of instances in the fixtures. This only works, of course, if the system has tests. Unfortunately, many of the systems that have serious coupling problems do not have tests, because the testing is too difficult.

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