What is in a name? On the misuse of information theoretic dispersion measures as design complexity metrics

Many metrics of design complexity have been proposed in the literature. Of these, the most popular are information theoretic metrics, such as information content based on Suh's axiomatic theory and differential entropy based on Shannon's information theory. In this paper, we show that these metrics do not provide common sense measures of complexity, and they also do not possess proper mathematical properties. At best, they are geared towards measuring a designs goodness-of-fit rather than its complexity. At least in part, the inappropriate use of these metrics can be attributed to misuse of terms such as 'entropy' and 'minimise information content'.