4 ms·
It depends on how it's been determined that it's the "typical worst case" ...maybe an anonymous usage program? ...maybe their typical use case? (which is defi
by dr_zoidberg 10y ago
It depends on how it's been determined that it's the "typical worst case"
...maybe an anonymous usage program?
...maybe their typical use case? (which is definitely not everyone elses)
...maybe the typical use case of Google employees using Go for their single-computer tasks? (which would be closer to a "typical user" as in people who read HN)
...an average of those three, or perhaps even more, use cases? wighted in some way?
But if done correctly, optimizing the 90% typical problem by 20%, gives you a general 18% improvement, far more than even making disappear the least important 10% of the runtime (which some bad optimization efforts tend to focus on...).
Making software faster is always about knowing where to work, and then focusing exactly on that. Nothing wrong in attacking the "typical [anything] case".