Programming has changed. In first generation languages like FORTRAN and C, the burden was on programmers to translate high-level concepts into code. With modern programming languages—I’ll use Python as an example—we use functions, objects, modules, and libraries to extend the language, and that doesn’t just make programs better, it changes what programming is.
Programming used to be about translation: expressing ideas in natural language, working with them in math notation, then writing flowcharts and pseudocode, and finally writing a program. Translation was necessary because each language offers different capabilities. Natural language is expressive and readable, pseudocode is more precise, math notation is concise, and code is executable.
But the price of translation is that we are limited to the subset of ideas we can express effectively in each language. Some ideas that are easy to express computationally are awkward to write in math notation, and the symbolic manipulations we do in math are impossible in most programming languages.
The power of modern programming languages is that they are expressive, readable, concise, precise, and executable. That means we can eliminate middleman languages and use one language to explore, learn, teach, and think.
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Interesting concept. The history of programming and programming language development (in my opinion) has been an attempt to make analysis/conceptualization more concrete and to make the coding constructs more conceptual with the hope that they will meet in the middle to reduce the transitions (and associated errors) in the life cycle–analysis->design->coding->deployment. I wrote an article in 1986 that touched on some of this. Although there have been incremental improvements, I think we still have problems in the transition from the front end of the life cycle to the middle and beyond–no programming language will solve that (languages don’t solve problems, people solve problems).