why are you using big O notation?
why are you using big O notation?
Here's the funny part: there is no such thing as O(10,000) in big O notation. Big O doesn't concern itself with constant factors, it's about how performance changes with the size of the dataset. If two algorithms run in constant time but one takes twice as long as the other (maybe it's a debug build), they aren't O(1) and O(2), they are both O(1).
So it's not surprising that anyone would be confused by O(10,000). In big O, this would be an impossible value. It just wouldn't make sense.
The best solution, as always, is to use plain English. You will never go wrong by saying "about 10,000".
"on the order of" 1000000 means any number from 1000001 through 9999999
I would expect "approximately" to mean accurate to within the next order of magnitude down. e.g. I would expect "approximately 500000" to mean a range of 400000 to 600000; maybe 350000 to 650000 if you're stretching it.
Not exactly. It can also mean anything from 500,000 to 4,999,999, or 316,228 to 3,162,277...
See https://en.m.wikipedia.org/wiki/Order_of_magnitude
But yeah, it doesn't mean approximately