Asymptotic computational complexity describes how the resource requirements of an algorithm or computational problem grow as input size increases. It is commonly expressed with notations such as Big O to compare time, memory, or other costs at scale while ignoring constant factors and lower-order terms.
In computational complexity theory, asymptotic computational complexity is the usage of asymptotic analysis for the estimation of computational complexity of algorithms and computational problems, commonly associated with the usage of the big O notation.