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'.

Original languageEnglish (US)
Pages (from-to)662-680
Number of pages19
JournalJournal of Engineering Design
Issue number9
StatePublished - Sep 10 2013


  • design complexity
  • differential entropy
  • information content
  • metric

ASJC Scopus subject areas

  • Engineering(all)


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