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Excerpt · Big-O Notation
We say algorithm A is O(n) and B is O(n²). Constants get washed out as inputs grow large.
O(n) means the work grows in direct proportion to input size. Double the data, double the time, the most common “fast enough” complexity for real-world algorithms.
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