cumulativehypotheses

mostly professional blather

Distribution of Complexity in jMock

Suppose we were to take methods one by one, at random and without replacement, from the source code of jMock 2. How would we expect the Cyclomatic Complexity of those methods to be distributed?

Here you will find some automation to discover the raw numbers, and here is a Mathematica Computable Document (get the free reader here) showing the analysis.

Result:

This evidence suggests that the Cyclomatic Complexity per method in this version of jMock is distributed according to a discrete power–law distribution with shape parameter ρ ≈ 1.92

Probability of Complexity of Methods in jMock 2

This chart shows the empirical probability of a given complexity in blue and that from the maximum–likelihood fitted power–law distribution in red. Solid lines show where the fitted distribution underestimates the probability of methods with a certain complexity occurring, dashed lines where it overestimates.

Note that both scales are logarithmic.

Other long-tailed distributions (e.g. log-normal) can be fitted onto this data, but the hypothesis that they represent data is rejected at the 5% level.

Written by keithb

August 17, 2011 at 2:01 pm

4 Responses

1. I can’t browse the source on bitbucket without a login. Is there a public URL for it?

Nat

August 17, 2011 at 3:35 pm

• Um, I’m confused. The “private repository” tickbox is un-ticked on that repo, but it still appears to be private. Could you try again now?

keithb

August 17, 2011 at 4:00 pm

2. Just guessing, the high complexity methods in JMock are mostly calls to ‘new’ right?

tcrayford

December 8, 2011 at 5:56 pm

• Before digging in to what the high complexity methods in JMock actually are like, could you expand on you thoughts? What’s behind your guess? I’m keen to understands what people’s intuition about this sort of thing is.

keithb

December 8, 2011 at 9:35 pm