Estimates the time difference in performance for recursive and iterative function in javascript. Using finabocci as a case study

finabocci.hs

recurse :: (Integral a) -> a -> a
recurse 1 = 1
recurse 0 = 1
recurse n = recurse (n-2) + recurse (n-1) 

-- refactoring
recurse :: (Integral a) -> a -> a
recurse n
    | n < 2 = 1
    | otherwise = recurse (n-2) + recurse (n-1) 

finabocci_iterative_recursive.js

function recurse(n) {
    if (n < 2) return 1;
    return recurse(n - 2) + recurse(n - 1);
}
// O(fib(n)) = O(φ^n) (φ = (1+√5)/2);

	function iterate(n) {
		if(n <= 1) {
			return n;
		}
		var fib = 1;
		var prevFib = 1;
		
		for(var i=1; i<n; i++) {
			var temp = fib;
			fib+= prevFib;
			prevFib = temp;
		}
		return fib;
	}

function memoizedRecurse() {
  memoizedValue = {};
  return function recurse(n){
    if(memoizedValue[n]) return memoizedValue[n];
    if (n < 2) return 1;
    f = recurse(n - 2) + recurse(n - 1);
    memoizedValue[n] = f;
    return f;
   }
}

function perf(times, func, msg) {
    const start = Date.now();
    for (let i = 0; i <= times; ++i) {
        func();
    }
    console.log(msg, 'Time taken to complete:', Date.now() - start, 'ms');
}
x = memoizedRecurse()
perf(10000000, () => recurse(10), 'Recursion');
perf(10000000, () => iterate(10), 'Iterative');
perf(10000000, () => x(10), 'memoizedRecursion');

Care to drop the Runtime Results?

You can simpy run the code on any browser to figure that out