The Shape of Code

Over the last few years software engineering academics have jumped aboard the power-law band-wagon (examples here and here). With few exceptions (one here) these researchers have done little more that plot their data on a log-log graph and shown that a straight line is a good fit for many of the points. What a sorry state of affairs.

Cognitive psychologists have also encountered straight lines in log-log graphs, but they have been in the analysis of data business much longer and are aware that there might be other distributions that are just as straight in the same places.

A very interesting paper, Toward an explanation of the power law artifact: Insights from response surface analysis, shows how averaging data obtained from a variety of sources (example given is the performance of different subjects in a psychology experiment) can produce a power law where none originally existed. The underlying fault could be that data from a non-linear system is being averaged using the arithmetic mean (I suspect that I have done this in the past), which it turns out should only be used to average data from a linear system. The authors list the appropriate averaging formula that should be used for various non-linear systems.