Big O Notation

Big O notation is a mathematical notation used to describe the limiting behavior of a function when the argument tends towards a particular value or infinity. In computer science, Big O notation is used to classify algorithms according to how their run time or space requirements grow as the input size grows. It provides a way to compare the efficiency of different algorithms by analyzing their worst-case scenarios. The notation expresses the upper bound of the growth rate in terms of a function of the input size, ignoring constant factors and lower-order terms. For example, an algorithm with a time complexity of O(n) means that the run time grows linearly with the input size, while an algorithm with a time complexity of O(n^2) means that the run time grows quadratically with the input size.
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