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Time complexity is an algorithm to find that how much time a algorithm will take to execute it
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Complexity defines the amount of time taken for processing the particular algorithm in terms of input. This is a measure to compare different algorithms for the same problem. If the complexity is low then the algorithm is efficient. It usually measure in terms of big O it only represents the degree of time taken for the algorithm. eg if two different algorithm takes n and n+100 then both have same time complexity 'n' in items of big O.
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Time complexity is an algorithm to find that how much time a algorithm will take to execute it.

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The time complexity of an algorithm is commonly expressed using big O notation, which excludes coefficients and lower order terms. When expressed this way, the time complexity is said to be described asymptotically, i.e., as the input size goes to infinity.

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Time complexity of an algorithm quantifies the amount of time taken by the algorithm to run 

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Time complexity is normally expressed as an order of magnitude, e.g. O(N^2) means that if the size of the problem (N) doubles then the algorithm will take four times as many steps to complete.

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