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3 points by shader 95 days ago | link | parent

> ... trading of programming theories ...

Clear and simple syntax / representation is important; combined with matching editing tools it enables us to communicate ideas easily and fluently.

I also like the idea of well defined input spaces. Many theorems or algorithms only work under certain conditions, and much damage has been done by applying them outside of their intended domains. But I think that's only part of the problem.

My own theory is that programs are specifications, and the more clearly and precisely they specify the better. Programs can fit into a matrix of good/bad ideas and good/bad specifications. Of these, two kinds are interesting bugs:

  1) Incorrectly specified good ideas
  2) Correctly specified bad ideas
Well specified good ideas are correct programs, and incorrectly specified bad ideas are just hopelessly confused.

Improving the languages and tools will never fix bad ideas, but they can make them more obvious. Now the goal is to make programming as close as possible to 'saying what you mean'. In other words, making the semantics as explicit as possible.

Basically my goal is 'declarative programming', which turns out to be a very vague concept to most people. They all agree that it's better, but nobody seems to have a good explanation for why. I think the difference is that declarative programs specify the only the relationships which are important, leaving the rest up to the platform to optimize or interpret as it sees fit. This leads to powerful and concise languages such as SQL, but at the cost of placing the burden on the platform rather than the programmer. Good for communication and clarity, bad for development and adoption.

Basically, declarative languages can be more concise because they rely more on shared knowledge; predefined vocabulary. If the language doesn't already have a way to express the concept you want, however, it is much more work to add. Imperative / procedural programs are more flexible because they rely on implicit semantics. You just tell the computer what to do—you don't have to explain what it is doing or why. Everything the program "accomplishes" is imaginary and external to the specification. This leaves very little room for the computer to optimize your selection of operations, and leaves a lot of room for you to accidentally provide an incorrect sequence of steps.

It's like the difference between giving directions by saying "Go to the grocery store at 5th and Main" vs. "Take a left, go three blocks, take a right, go two more blocks, park on the right side of the street and enter the blue building." The first is much clearer, but places much higher expectations on the navigation abilities of the recipient, while the second can be followed by anyone even though they have no idea where they're going - and mistakes are correspondingly harder to notice.

Sadly, the nature of declarative languages makes them fairly domain specific, which may explain part of why they're so rare and hard to make. Creating a declarative language for solving a class of problems is much harder than solving a single problem imperatively; you actually have to think of how and why you're solving those problems. But I think we could probably create some general patterns and guidelines for defining them, and maybe even start building up some tools to reduce the effort required.