What algorithm did Windows XP use to choose your initial user picture?

Its not like windows is the pinnacle of software craftsmanship.

Programming for MCUs. Less so today when multi-hundred MHz MCUs are cheap, but even several years ago there were a lot of products where you needed to use the cheapest MCU and everything it did had to be optimized to avoid stalls and edge cases.

Second is doing LeetCode problems for fun/practice. This will elicit a groan from a lot of people, but the algorithms and pathological edge cases you learn really do change your thinking. The most interesting ones are the hard problems where they’ve added some hidden test case that causes naive solutions and algorithms to blow up. You start thinking on high alert for edge cases and Big O problems. It’s more fun when you’re doing it to learn on your own than for forced interview prep.

Being tenured and one of the top engineers in your company with a very proven track record gives you quite a bit more freedom.

https://jakeludington.com/2003/12/17/create_your_own_windows...

On top of that, how often is it necessary to efficiently know the number of files in a directory while at the same time not caring about the files enough to list or display them? This algorithm is a special case where you could use the count of using a bit simpler code that ultimately would have the same file system API calls (since you cannot tell the FS to give you file #37 from that directory, so you'd have to use FindNextFile 37 times anyway, just like the sampling algorithm).

I don't know if they've relaxed this since the days of non-FPU CPUs - anyone know? If they let the Weather app use a webview, there must be some floating point usage in there.

This code is at a much higher level though - at the user shell level, explorer.exe.

Anyways, asking Google's AI to remove the above code's use of floating point results in code resembling the original version.

Trying to best Windows devs on performance becomes almost comical if you read the comment for the RtlRandomEx:

    it is faster than RtlRandom() since it saves one multiplication, one addition and
    one modulus operation. This almost doubles the performance since it halves the number of
    clocks even on a pipelined Integer Unit such as the P6/ia64 processors i.e. ~ 52% perf gain.

You still need to see all of the items once.

Imagine you have 2 items.

First one has 100% chance to be selected. So it does. Then the second has 50% chance to be selected. If it isn’t you effectively chosen the first one and have 50/50 chance to return either.

Now you add a third item. There is 50/50 chance of having either selected. And 1/3 chance of replacing the selection with the new one. Resulting in a 1/3 chance of selecting any of the three. (Because 1/2-1/6 = 1/3) 1/6 because there is 50% chance you will “steal” the selection.

I didn't get it at first, either, and the Wikipedia article didn't do it for me. This explanation finally got me there: https://florian.github.io/reservoir-sampling/

Different teams with different goals and different management

I get what you mean, but it's really hard for any organization this size to drive consistent quality across the board.

Yep..

And image files were, and continue to be, a huge exploit attack vector

Just like the rest of us.