I was considering ASM's for it: http://pages.di.unipi.it/boerger/Papers/Methodology/BcsFacs07.pdf http://pages.di.unipi.it/boerger/Papers/Methodology/BcsFacs0.

I was considering ASM's for it: http://pages.di.unipi.it/boerger/Papers/Methodology/BcsFacs07.pdf http://pages.di.unipi.it/boerger/Papers/Methodology/BcsFacs0... My thinking was like this. The complexity of software is synonmyous with us saying we don't know what it will do on given inputs. As complexity goes up, it gets more unpredictable. That's because of the input ranges, branching, feedback loops, etc. So, a decent measure of complexity might be simplifying all that down to purest form that we can still measure. The ASM's are a fundamental model of computation basically representing states, transitions, and conditionals making them happen. So, those numbers for individual ASM's and combinations of them might be good indicator of complexity of an algorithm. And note that they can do imperative and functional programming. What you think of that idea?