I was writing an event handler function and realized that I was coding loops in a way that is not usually possible in other languages. Lets discuss this technique, which can help improve the run-time of certain iterative for loops.

Suppose you have an event callback function with multiple triggers and a collection of something that you need to iterate through each time the callback function is made (like rows in a table or list items in a list). You then need to do something different to the collection depending on what trigger hit the callback function. In most languages you would have a for loop containing a switch statement with N cases (or if statements if you absolutely cannot use a switch). Here is an example that executes a function on each list item depending on the trigger id:

function callback(e) {
	var items = document.body.getElementsByTagName(li);
	var trigger = Event.getTarget(e); // this is a Framework function that is really useful	
	var id = trigger.id;
	for (var i=0, j=items.length; iid1:
				someFunctionForId1(items[i]);
				break;
			case id2:
				someFunctionForId2(items[i]);
				break;
			case id3:
				someFunctionForId3(items[i]);
				break;
			case id4:
				someFunctionForId4(items[i]);
				break;
			default: // any other id
				someFunctionForId5(items[i]);
				break;
		}
	}
}

This is perfectly valid code and will work great on small sets, because the switch statement has a very small run-time cost (switches are very quick seek structures in JavaScript), and on a small set, you will not execute the statement many times. The runtime as an equation would be:

k1 * n = r
where k1 = the constant cost of the switch
n = the number of values in the array
and r = run-time

There is a better way to write this function, where the select statement is only executed once:

function callback(e) {
	var items = document.body.getElementsByTagName(li);
	var trigger = Event.getTarget(e); // this is a Framework function that is really useful	
	var id = trigger.id;
	var fx = null;
	switch (id) {
		case id1:
			fx = someFunctionForId1;
			break;
		case id2:
			fx = someFunctionForId2;
			break;
		case id3:
			fx = someFunctionForId3;
			break;
		case id4:
			fx = someFunctionForId4;
			break;
		default: // any other id
			fx = someFunctionForId5;
			break;
	}
	for (var i=0, j=items.length; i
For this callback the runtime is:
(k2 + k1) + (c * n) = r
where k1 = the constant cost of the switch
k2 = the constant cost of assigning the function to variable fx
c = the cost of seeking and executing the function fx
n = the number of values in the array
and r = run-time
I have not done the actually runtime analysis, so I do not have the exact numbers, but you should not have to stretch your imagination far to assume that the cost of c < k1, so as long as the number of iterations (n) are overwhelm the constant (k1 + k2), then the latter algorithm is faster. The exact equation for this comparison is:
(k1 + k2) + (c * n) = k1 * n
where k1 = the constant cost of the switch
where k2 = the constant cost of assigning the function to variable fx
c = the cost of seeking and executing the function fx
n = the number of values in the array
computing for n, you get:
n = (k1 + k2) / (k1 - c)
If you have time, try profiling some loop code to figure the exact numbers. My assumption is that n is between 10 & 20, so anytime I iterate on a list greater than 10 and can use this pattern, I do.