The UI toolkit without screenshots.
The scientific paper without reproducible environment.
The deep learning models with no weights.
The optimizer without benchmarks.
The scientific paper without reproducible environment.
The deep learning models with no weights.
The optimizer without benchmarks.
The idea of superoptimization is to find missed optimizations, which a human can review and then implement directly.
That sounds measurable.
Can it optimize sequences of shuffles? If so, it'd be worth a try, even if it takes hours (probably doesn't take that long?), I could let it run until it finds faster sequences than what I have now, and update my code.
But for it to be worth the time for me to figure out how to install and use it, I need some sort of expectation for what I'd get out of trying this instead of something else.
Example program 6: https://www.cs.utah.edu/~regehr/souper/output_6.html
int a, b;
void fn1() { b = a * ~1 == 1; }
By its nature Souper becomes less effective over time as its findings are incorporated into LLVM, so most of the trophies are old!
The new programming language without sample code on the landing page.
Anyway, at least the big Get Started button points to some code.
Besides, over half of website use is via mobile nowadays.
Compiling and profiling reasonably complex apps against baseline would be enough.