there are continuous programming languages out there - DNA is one such one i guess. But i don't think the discrete vs continuous nature of a programming language is what makes it difficult. It's more that a person's mind may not conceptualize tasks algorithmically, and to switch to this frame of mind is difficult for someone who isn't already in this frame of mind.
That's a good point. DNA as a programming language has to be at least somewhat continuous, or else evolution has nothing to optimize because every change has a random effect.
DNA is a lot less discrete that you might think. There's epigenetic factors and population proportions, for example.
But even considering DNA as just a 4-letter language with discrete characters, my point is that many, even most, small sequence changes to a genome (e.g. single-nucleotide variants) have small effects or no effect at all, which gives evolution a smooth enough gradient to optimize things over time. That's what I mean by continuous in this context. The opposite would be, for example, a hash function, where any change, no matter how small, completely changes the output. Hence you couldn't "evolve" a string with a hash of all 7s by selecting for "larger proportion of 7s in the hash function", because hash functions are completely discontinuous by design. But you can evolve a bacterium that includes more of a given amino acid in its proteins by selecting for "larger proportion of that amino acid in protein extract".
