You can probably just compare AOT and JIT Java or C# implementations and get something of an upper bound.
Actual improvements will likely depend on your use case: for short-running programs the overhead of the parsing, JIT machinery & interpretation might dwarf the execution time so even a straightforward compilation full of virtual calls will edge out the pre-JIT interpreter, however for longer-running programs the JIT should be able to devirtualise, inline and optimise the code much better than the AOT compiler will.
Inlining is the most important optimisation, and it's hard to AOT inline dynamic dispatch.
But a lot of JS code executes only once, such as layout code running at app launch. Heck, lots of JS code executes zero times. This code still imposes a cost (parsing, etc).
Consider the complaints about app launch time of Electron apps. A static compiler can be more effective at the runs-once or runs-zero cases.
The difference is that you compile user control flow as-is unless you have overwhelming evidence that you should do otherwise.
And yes you are right. This is promising for run-once code, but all of the cost will be in dynamic things like the envGet. An interpreter can actually do better here because most environment resolution can be done as part of bytecode generation. So it’s possible that this experiment leads to something that is slower than JSC’s interpreter.
It is possible to statically decide which environment contains each upvar. So I don't understand your conclusion that this experiment may be slower than JSC's bytecode interpreter. What information can JSC exploit at this stage that is statically unavailable?
JSC has speculations that eval won’t introduce variable names we’ve already resolved for example.
https://v8.dev/blog/launching-ignition-and-turbofan https://v8.dev/blog/v8-release-66 https://v8.dev/blog/background-compilation
Tracing and other dynamic analysis can do a lot to improve the quality of generated code -- it's effectively a realtime PGO. On the other hand, there's a substantial activation energy in the form of the initial lex, parse, AST generation/manipulation, interpretation and dynamic analysis, re-optimization, etc. that can all be handled ahead of time, albeit with less information to optimize.
Which modern JS engine still relies on tracing? I thought they’d all moved on from that technique many years ago, but I’m not an expert in JS.
Pre-parsing is an obvious big win, but there's also classical compiler optimizations: constant propagation, DCE, certain inlining, etc. Local variables can be statically determined to be non-captured, which means they can be stack allocated.
One totally bizarre but profoundly useful property of JS is the restrictions on eval. eval has the ability to run new code, but this code is globally scoped unless it's run as the "eval" function itself. [1] Thus it's easy to decide which local variables are immune to eval; this in turn unlocks lots of optimizations. To my knowledge this weirdo behavior is not present in Python or other dynamic languages.
In JS functions are first class, so one might attempt:
function wut() {
var x = 1;
var obj = {sneaky: eval};
obj.sneaky("x++");
console.log(x);
}
The answer is no: because the caller's name 'obj.sneaky' does not literally compare equal to "eval", the eval function is run with global scope instead of local scope. Therefore the 'x' inside the eval'd string is a global property, not the local variable.
So with this analysis we can (statically) apply constant propagation and replace x with 1.
Now if we replace obj.sneaky with eval, the string comparison succeeds, it becomes "direct eval", and the constant propagation is invalid.
There's workarounds like "(1, eval)", but the most idiomatic way is the Function constructor, which always runs code at global scope. That leads to this pattern:
var global = (new Function("return this")())
But maybe there will be some breakthrough, so it’s important to stay open-minded. That breakthrough may be something modest like if this style of JS execution was better for some niche use case.