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Any iterative algorithm could compound its own rounding errors until the final result is nonsense. This created the need for a theory of https://en.wikipedia.or

Any iterative algorithm could compound its own rounding errors until the final result is nonsense. This created the need for a theory of https://en.wikipedia.org/wiki/Numerical_stability https://en.wikipedia.org/wiki/Numerical_stability and tweaking algorithms to do the same things in a different order that happens to blow up less often. In some ways fixed point would be safer or at least more predictable.

jqpabc123 5y ago
In some ways fixed point would be safer or at least more predictable. Outside a laboratory setting, there are very few real world problems that can't be adequately addressed with scaled integers (fixed point math). Most things have practical limits imposed on accuracy. Most monetary transactions are legally required to be settled in pennies (at least in the US). Most time periods are recorded in minutes or seconds. Most thermometers are only accurate to 1/10 of a degree. Attempting to exceed these practical, real world limits is really just "false accuracy" that causes more problems than it solves.