Misuse of Information-Theoretic Dispersion Measures as Design Complexity Metrics
Complexity is defined as a quality of an object with many interwoven elements, aspects, details, or attributes that makes the whole object difficult to understand in a collective sense. Many measures 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 Entropy based on Shannon’s Information Theory. In this paper we will show that not only these metrics do not provide common sense measures of complexity, but they also do not possess proper mathematical properties. At best, they are geared towards measuring a designs goodness of fit rather than its complexity. It is hoped that this paper will generate some debate on strongly held beliefs in the design theory community.