Examples of algorithms and explanation for each Big O Notation category.
Some examples are based in this video. If you didn't manage to understand Big O Notation yet, would be an excellent choice to watch it.
In order to run these scripts, you'll need to have Go (preferably 1.16) installed.
You can run an example by typing go run example.go to any script in the categories folder.
An algorithm is said to be constant time (also written as O(1) time) if the value of T(n) is bounded by a value that does not depend on the size of the input. For example, accessing any single element in an array takes constant time as only one operation has to be performed to locate it. In a similar manner, finding the minimal value in an array sorted in ascending order; it is the first element. (source)
Example: constant_time.go
An algorithm is said to take linear time, or O(n) time, if its time complexity is O(n). Informally, this means that the running time increases at most linearly with the size of the input. More precisely, this means that there is a constant c such that the running time is at most cn for every input of size n. For example, a procedure that adds up all elements of a list requires time proportional to the length of the list, if the adding time is constant, or, at least, bounded by a constant.
Example: linear_time.go