Respuesta :
Time efficiency is a measure of how long it takes an algorithm to execute and can be used to gauge the method's efficiency.
Also, space efficiency is a measure of the amount of memory required for an algorithm to perform. When n is large, asymptotic dominance is used to compare cost functions. That is, if g dominates f for all "big" values of n, g asymptotically dominates f.
Explanation in detail:
The efficiency of an algorithm refers to how quickly it can deliver the correct solution to a given problem. The efficiency of an algorithm is determined by its time and space complexity. The complexity of an algorithm is a function that delivers the running time and storage space based on the size we specify.
There are usually natural units for the domain and range of this function. There are two basic complexity metrics of an algorithm's efficiency: Time complexity is a function that describes how long an algorithm takes in terms of the quantity of input it receives.
Algorithm complexity is a metric that analyzes the order of the number of operations executed by a given algorithm as a function of input data size. To put it another way, complexity is a rough estimate of the number of steps required to execute an algorithm.
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