Web Reference: Mar 28, 2026 · Big-O is a way to express an upper bound of an algorithm’s time or space complexity. Describes the asymptotic behavior (order of growth of time or space in terms of input size) of a function, not its exact value. Can be used to compare the efficiency of different algorithms or data structures. Big O, also known as Big O notation, represents an algorithm's worst-case complexity. It uses algebraic terms to describe the complexity of an algorithm. Big O defines the runtime required to execute an algorithm by identifying how the performance of your algorithm will change as the input size grows. But it does not tell you how fast your algorith... This webpage covers the space and time Big-O complexities of common algorithms used in Computer Science.
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