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Welcome back.

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Let's talk about the very first roll when it comes to big oil, that is worst case when calculating

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big oh, we always think about the worst case.

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What do I mean by that?

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Well, if we go back to Finding Nemo example.

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And the Find Nemo function.

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You may have been screaming at me while I was going through the function saying that, Andre, this

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is not efficient.

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What are you doing?

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Because if you look at this function, we're looping through the entire array to find Nemo.

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Remember how we had the everyone tray with about 10 different characters from Finding Nemo?

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Well, Nima was only the one, two, three fourth member on this array, and when we run this function.

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We found Nemo, but the funny thing is this function ran 10 times, not four times.

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If I do a console log here and I say.

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Running and let's click this.

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We see that this function ran one, two, three, four, five, six, seven, eight, nine, 10.

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Hmm.

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I mean, we already found nimo.

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All these runs are pretty wasteful.

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So we can make this function a little bit more efficient in JavaScript, we can just have something

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called break.

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And again, different languages have different ways of exiting out of a loop if a condition is met.

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In our case, if we find Nemo, just break out of this loop.

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If I do this and click run.

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Look at that, once we found Nemo, we're done, we're not going to loop through the rest of the items.

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Congratulations, we just made our code a little bit more efficient.

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That's a good thing, right?

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Well, when it comes to Big O, although this is important and when you write good code, this is something

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that we want to do in the big scheme of things.

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Bigo only cares about the worst case.

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What is the worst case here?

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Well, the worst case is that nimo, instead of being the fourth item is at the very end.

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So even if we have this brake statement, we're still going to run this 10 times because nimo at the

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end, best case is if Nemos at the very beginning and we only have to live through it once.

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But worst case, we're still going to have to go through 10.

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Loops still big o of nd so this is our very first rule, the very first rule is we always care about

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what is the worst case scenario, because when we talk about scalability, we can't just assume things

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are going well, even though the Find Nemo function might be of one if Nemo.

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Is the very first item in the array.

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It doesn't matter in the grand scheme of things, because we can't be certain of what the input is going

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to be, we're going to assume that of Bigo is of non linear time.

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Again, if we're finding a yellow box.

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And the yellow box is at the very end, we have to iterate through all the boxes.

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If the yellow box at the very beginning, you see that we don't have to iterate through these boxes.

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But Bigo doesn't really care, even though this function, yes, is indeed more efficient, at the end

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of the day, when we talk about Bigo, we're talking about worst case.

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All right, I hope you got that point, too, I feel like I've beaten to a pulp, so you should be comfortable

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with it by now.

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Let's talk about the next role on the next video.