[paliilap]

I take your point that these are two separate concerns, and we do certainly see a) without b) with Numpy, Julia, Matlab, R and the like. Using these languages is a very productive experience, and I agree that a) is definitely the main driver.

With J and APL, one pragmatic benefit I do see of the symbols over the words is the ability to see and use patterns if one is familiar with the language. This is harder to do with the words, which spread concepts thinner. I think Iverson expresses these ideas very nicely in Notation as a Tool of Thought.

The APL/J/K family strongly assume that readers of the language are familiar with their parsing and semantics, so idiomatic usage of each language makes no concessions for what is felt to be unnecessary. It's a different mindset for sure. When the users of the language share an understanding of what the symbols mean though, they no longer think it's obfuscated.

J takes such strong inspiration from English (to the point that it calls functions "verbs", operators "adverbs" and "conjunctions", and arrays "nouns"), that I once thought J would be better written entirely as English words instead. After having made such attempts, I actually found it harder to read and maintain the English versions. I couldn't attach strict behaviour and meaning to the words like I could with the special symbols. Perhaps I didn't entertain this idea long enough, but the words felt considerably less malleable.

[StreamBright]

I see your point, the ability of taking in symbols that are used in math as they are (quite often Greek alphabet letters) makes the syntax more familiar to people who are in this field.

That is interesting that you have this experience with maintaining the two versions. I guess I should try it out as well.