Linear

Linear time complexity, denoted as O(n), is one of the best possible algorithmic performance situations. An algorithm is said to have a linear time complexity when the running time increases at most linearly with the size of the input data. This means that if you double the size of the input, the running time will at most double as well. In an ideal situation, every single element in the data set should be viewed exactly once. Sorting algorithms such as counting sort and bucket sort have linear time complexity under certain conditions.