Measure software - and its evolution - using information content
Tom Arbuckle · 2009
To be able to examine software evolution - variation in software over a sequence of releases - or to compare differing versions of software with each other, we need to be able to measure artefacts representative of the software or its creation process. One can find in the literature a multitude of approaches to both measuring software - by defining and applying software metrics - and to examining software evolution in terms of these metrics. In this position paper, we claim that information content, specifically the (relative) Kolmogorov complexity, is the correct and fundamental tool for the measurement of software artefacts. Experimental results obtained from an analysis of the project udev demonstrate utility: future work should explore the breadth of applicability and determine the full scope of the approach.