Big O Notation — How Algorithm Cost Scales
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YouTubeO(Briefs)
Big O Notation — How Algorithm Cost Scales
Big O notation describes how an algorithm's cost grows as input size grows — not how fast it runs on your machine today. O(1) stays flat, O(log n) barely climbs, O(n) scales linearly, and O(n²) explodes. O(Briefs) maps all four onto a single graph so you can read complexity at a glance.
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