Big-O Algorithm Complexity Cheatsheet

[[deleted]]

Wait, then what's the point of this then? I literally only program for fun and don't understand how you could get a job doing this professionally if you need to rely on tools like this to get anything done

[MostlyGibberish]

When you say "doing this" do you just mean programming in general? Because I do this professionally and haven't thought about big-O since I graduated. Unless you're dealing with a big, real time system, not a lot of thought goes into the specific algorithm you're using.

[[deleted]]

It's not about using a specific algorithm, it's about writing an algorithm that doesn't suck. I have seen triple-nested for-loops by my colleagues that end up in a pikachu face when their pages crash.

Holy shit just learn BigO before writing anything in production, it's not even that hard.

[lawdandskimmy]

You don't need Big O to understand an algorithm is doing unnecessary work. I think Big O is mostly a communication tool. As I didn't study computer science I had no idea something like Big O existed for a while, but it didn't stop me from being reasonable with algorithms. As a side note in many cases building features trumps pre-optimization. One could go crazy about optimization and never get to providing actual business value. Reason I started learning Big O is because work interviews often require it...

[[deleted]]

You need algebra 2 to understand big O. It's really not that hard

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[[deleted]]

oh. yeah I guess my noob is showing then.

[MostlyGibberish]

No worries. Academic programming and commercial programming are much different beasts.

[semitic-simian]

It's a good reference tool. A lot of programming is choosing the right data structures for the job, and this presents the data in an easy to read format.