GrößerOhNotation
GrößerOhNotation, commonly referred to as Big O notation, is a mathematical notation used in computer science to describe the performance or complexity of an algorithm. Specifically, it characterizes functions according to their growth rates. When an algorithm is described as having a Big O complexity of O(f(n)), it means that as the input size 'n' grows, the algorithm's execution time or space requirements will grow no faster than a constant multiple of f(n).
The purpose of Big O notation is to provide an upper bound on the growth rate of
Common Big O complexities include O(1) (constant time), O(log n) (logarithmic time), O(n) (linear time), O(n log