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A visual introduction to big O notation

(samwho.dev)
688 points samwho | 6 comments | 24 Aug 25 07:39 UTC | HN request time: 0.872s | source | bottom
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dawnofdusk ◴[25 Aug 25 18:41 UTC] No.45017382[source]▶
Whenever I read content like this about Big O notation I can't help but think the real solution is that computer science education should take calculus more seriously, and students/learners should not dismiss calculus as "useless" in favor of discrete math or other things that are more obviously CS related. For example, the word "asymptotic" is not used at all in this blog post. I have always thought that education, as opposed to mere communication, is not about avoiding jargon but explaining it.
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1. crystal_revenge ◴[25 Aug 25 19:27 UTC] No.45017900[source]▶
> students/learners should not dismiss calculus as "useless"

This seems to be quite a bit of a strawman to me.

ML is such a major part of the field today and at a minimum requires a fairly strong foundation in calc, linear algebra, and probability theory that I earnestly don't believe there are that many CS students who view calculus as "useless". I mean, anyone who has written some Pytorch has used calculus in a practical setting.

Now in pure software engineering you will find a lot of people who don't know calculus, but even then I'm not sure any would decry it as useless, they would just admit they're scared to learn it.

If anything, I'm a bit more horrified at how rapidly peoples understanding of things like the Theory of Computation seem to be vanishing. I've been shocked with how many CS grads I've talked to that don't really understand the relationship between regular languages and context free grammars, don't understand what 'non-determinism' means in the context of computability, etc.

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2. dawnofdusk ◴[25 Aug 25 19:43 UTC] No.45018105[source]▶
>This seems to be quite a bit of a strawman to me.

Not really, if you ever listen to CS undergrads or people in non-traditional schooling (bootcamps, etc.) talk about software engineering this opinion is essentially ubiquitous. People interested in ML are less likely to hold this exact opinion, but they will hold qualitatively identical ones ("do you really need multivariable calculus/linear algebra to do ML?"). It is precisely because people (primarily Americans) are scared to learn mathematics that they rationalize away this fear by saying the necessary mathematics must not be essential, and indeed it is true that many people get away without knowing it.

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3. marcosdumay ◴[25 Aug 25 20:03 UTC] No.45018325[source]▶
Most people from almost every specialty mostly dismiss calculus as useless, don't even remember linear algebra is a thing, and never learn or forgets everything about statistics. (But the reaction to probability varies a lot.)

I have no idea what's up with those disciplines, but it's an almost universal reaction to them. Unless people are very clearly and directly using them all the time, they just get dismissed.

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4. samwho ◴[25 Aug 25 20:25 UTC] No.45018560[source]▶
Can’t imagine what it might be.
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5. the_af ◴[25 Aug 25 21:08 UTC] No.45019028[source]▶
> non-traditional schooling (bootcamps, etc.)

It's probably unfair to qualify those as "computer science education" though...

6. marcosdumay ◴[26 Aug 25 17:05 UTC] No.45029360{3}[source]▶
If that's sarcastic, do you have any idea why probability is different?