The appropriate Big O notation for the complexity of a search algorithm depends on the specific algorithm being used. However, in general, the most commonly used Big O notations for search algorithms are O(log n) and O(n).
O(1) represents constant time complexity, which is not typically associated with search algorithms. It means that the algorithm has a constant execution time, regardless of the size of the input.
O(log n) represents logarithmic time complexity, which is commonly seen in binary search algorithms. It means that the execution time increases logarithmically with the size of the input.
O(n) represents linear time complexity, which is commonly seen in linear search algorithms. It means that the execution time increases linearly with the size of the input.
O(n^2) represents quadratic time complexity, which is not typically associated with search algorithms. It means that the execution time increases exponentially with the size of the input.
Therefore, O(log n) and O(n) are the most appropriate Big O notations for the complexity of a search algorithm.
which of the following Big O notations is the appropriate for the complexity of a search algorithim
O(1)
O(log n)
O(n)
O(n^2)
1 answer
1 answer