Albert Y. C. Lai trebla at vex.net
Tue Jan 17 01:54:58 UTC 2017

```There is an idea called "open recursion". Illustrating by Fibonacci (the
direct but naively slow way) and factorial (the direct but naively slow
way again, see
http://www.luschny.de/math/factorial/FastFactorialFunctions.htm
):

Instead of writing "fac x = x * fac (x-1)", we write:

fac x = fac_essence fac x

fac_essence f 0 = 0
fac_essence f x = x * f (x-1)

And instead of writing "fib x = fib (x-1) + fib (x-2)", we write:

fib x = fib_essence fib x

fib_essence f 0 = 0
fib_essence f 1 = 1
fib_essence f x = f (x-1) + f (x-2)

The general pattern: Write a helper essence function that takes one more
parameter, a function parameter; don't recurse yet, use the function
parameter instead. Leave the recursion to the main function.

Why would we do this?

One reason is philosophical, like you said, to factor out the recursion
from the essence of one iteration of the process.

Another reason is that you don't have to merely put back the recursion
in the main function. You can now play some dependency injection trick
before recursing, or maybe you don't even recurse.

For example, how about injecting a dependency on a lookup-list, with the
content of said lookup-list coming from said injection --- there hides
the recursion.

fib_list = [fib_essence (fib_list !!) i | i <- [0..]]

or maybe you prefer

fib_list = map (fib_essence (fib_list !!)) [0..]

You will find that "fib_list !! 100" is less slow than "fib 100".

Sometimes you prefer a function-application interface. So we go on to write:

fib_notslow x = fib_list !! x

In fact sometimes we turn it around, hide away the lookup table, and write:

fib_notslow = (fib_list !!)
where
fib_list = [fib_essence fib_notslow i | i <- [0..]]
-- I could write "fib_essence (fib_list !!)",
-- but now that (fib_list !!) has a name, "fib_notslow"...

Thus we have obtained a revisionist-history definition of dynamic
programming and memoization: Dependency injection of a lookup table into
a recursion.

List is still not fast enough; a binary search tree (lazily generated)
is even better. The "memoize" library