Would moving the inner function outside of this one so that its not created everytime the function is called be a micro-optimisation?
In this particular case the
The original question was asked in 2011. Given the rise of Node.js since then, I thought it's worth revisiting the issue. In a server environment, a few milliseconds here and there can matter a lot. It could be difference between remaining responsive under load or not.
While inner functions are nice conceptually, they can pose problems for the JavaScript engine's code optimizer. The following example illustrate this:
function a1(n) {
return n + 2;
}
function a2(n) {
return 2 - n;
}
function a() {
var k = 5;
for (var i = 0; i < 100000000; i++) {
k = a1(k) + a2(k);
}
return k;
}
function b() {
function b1(n) {
return n + 2;
}
function b2(n) {
return 2 - n;
}
var k = 5;
for (var i = 0; i < 100000000; i++) {
k = b1(k) + b2(k);
}
return k;
}
function measure(label, fn) {
var s = new Date();
var r = fn();
var e = new Date();
console.log(label, e - s);
}
for (var i = 0; i < 4; i++) {
measure('A', a);
measure('B', b);
}
The command for running the code:
node --trace_deopt test.js
The output:
[deoptimize global object @ 0x2431b35106e9]
A 128
B 130
A 132
[deoptimizing (DEOPT eager): begin 0x3ee3d709a821 b (opt #5) @4, FP to SP delta: 72]
translating b => node=36, height=32
0x7fffb88a9960: [top + 64] <- 0x2431b3504121 ; rdi 0x2431b3504121
0x7fffb88a9958: [top + 56] <- 0x17210dea8376 ; caller's pc
0x7fffb88a9950: [top + 48] <- 0x7fffb88a9998 ; caller's fp
0x7fffb88a9948: [top + 40] <- 0x3ee3d709a709; context
0x7fffb88a9940: [top + 32] <- 0x3ee3d709a821; function
0x7fffb88a9938: [top + 24] <- 0x3ee3d70efa71 ; rcx 0x3ee3d70efa71
0x7fffb88a9930: [top + 16] <- 0x3ee3d70efab9 ; rdx 0x3ee3d70efab9
0x7fffb88a9928: [top + 8] <- 5 ; rbx (smi)
0x7fffb88a9920: [top + 0] <- 0 ; rax (smi)
[deoptimizing (eager): end 0x3ee3d709a821 b @4 => node=36, pc=0x17210dec9129, state=NO_REGISTERS, alignment=no padding, took 0.203 ms]
[removing optimized code for: b]
B 1000
A 125
B 1032
A 132
B 1033
As you can see, function A and B ran at the same speed initially. Then for some reason a deoptimization event occurred. From then on B is nearly an order of magnitude slower.
If you're writing code where performance is importantly, it's best to avoid inner functions.