Do you find cyclomatic complexity a useful measure?

Question

I\'ve been playing around with measuring the cyclomatic complexity of a big code base.

Cyclomatic complexity is the number of linearly independent paths through a pr

Answer 1

Actually, cyclomatic complexity can be put to use beyond just method level thresholds. For starters, one big method with high complexity may be broken into several small methods with lower complexity. But has it really improved the codebase? Granted, you may get somewhat better readability by all those method names. But the total conditional logic hasn't changed. And the total conditional logic can often be reduced by replacing conditionals with polymorphism.

We need a metric that doesn't turn green by mere method decomposition. I call this CC100.

CC100 = 100 * (Total cyclomatic complexity of codebase) / (Total lines of code)

Answer 2

You'll know complexity when you see it. The main thing this kind of tool is useful for is flagging the parts of the code that were escaping your attention.

Answer 3

We recently started to use it. We use NDepend to do some static code analysis, and it measures cyclomatic complexity. I agree, it's a decent way to identify methods for refactoring.

Sadly, we have seen #'s above 200 for some methods created by our developers offshore.

Answer 4

It's great for help identifying candidates for refactoring, but it's important to keep your judgment around. I'd support kenj0418's ranges for pruning guides.

Answer 5

I'm afraid that for the language of the project for which I would most like metrics like this, LPC, there are not, in fact, lots of free tools for producing it available. So no, not so useful to me.

Answer 6

After understanding what it means, I now have started to use it on a "trial" basis. So far I have found it to be useful, because usually high CC goes hand in hand with the Arrow Anti-Pattern, which makes code harder to read and understand. I do not have a fixed number yet, but NDepend is alerting for everything above 5, which looks like a good start to investigate methods.