# What are some common conversational terms used when discussing the BigO notation?

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What are some common conversational terms used when discussing the BigO notation?

I think this wold be a good way to give me more exposure to learn the meaning of common terms used when discussing the BigO notation.

Please provide as many as come to mind...

Thanks
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Glanced up at my screen and thought I had coded the Matrix...  Turns out, I just fell asleep on the keyboard.
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Commented:
Unless your talking to students in your Comp. Sci. class, it's rare to discuss big-O in the real world. (By real-world, I mean more the line-of-business sector. Maybe in video game design or NASA/Tesla they care more about big-O.) That said, "memoization" is a term I remember from class. The different kinds of growth--exponential, linear, logarithmic, etc.--are relevant.
Commented:
1. If n is a very large number, so large that the Big Oh notation is applicable, then what happens to the performance or number of operations if n is doubled?
2. Your algorithm sucks. Big Oh is O(n-cubed), and I read that we should be able to get it down to O(n-squared). Don't go home until you come up with the algorithm and analysis report proving I am right.

Commented:
>> it's rare to discuss big-O in the real world
What, you don't discuss big-O with your drinking buddies!! Come on, confess up.
Glanced up at my screen and thought I had coded the Matrix...  Turns out, I just fell asleep on the keyboard.
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Commented:
XD
Commented:
I assumed this was for loose conversation within a computer algorithm oriented project.

3. You tell me that we get good performance O-log(n), but you didn't tell me what the constants are. For our needs, we'd be better off with O(n log n) with a much smaller constant. If we expand 1000 times in the future, we can reconsider, but practically speaking, your analysis although correct, is not applicable to our current needs.

4. What is the value N, such that n > N for your expression of Big-Oh to be applicable?
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