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A visual introduction to big O notation

(samwho.dev)
688 points samwho | 1 comments | 24 Aug 25 07:39 UTC | HN request time: 0.001s | source
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ChicagoDave ◴[26 Aug 25 13:49 UTC] No.45026541[source]▶
I liked the presentation (right or wrong), but wanted to point out I’ve been in IT as a coder and architect for 40 years and never once needed to know big O notation.

Which I think is the complaint here. The article author might have made an effort to connect it’s significance to Internet solutions like Search.

I assume he didn’t because that’s already been done.

replies(2): >>45026762 #>>45028104 #
1. mock-possum ◴[26 Aug 25 15:42 UTC] No.45028104[source]▶
fwiw I’ve been writing code for 2 years and I have occasionally benefitted from half-remembering the concepts that big O notation describes (even though my memory of the proper terminology is pretty shoddy, it’s been a long time since we covered it in college)

When new releases of website features have resulted in notably poor performance, and profiling has revealed a particular function taking time on the order of seconds to complete (seconds are an eternity in UI land) it’s important to be able to reach into code that processes big chunks of data, and identify loops-within-loops-within-loops that could be rearchitected to play out more efficiently.

Knowing that you’re going from O(n^2) to O(2n) is really just a matter of jargon - knowing that your list of results now displays in 1/10th the time, and why, is still pretty important. The underlying logic/math is the important bit to have a concept of, imo, big O is just a fun way to talking about it.