In linear search, best-case complexity is O(1) where the element is found at the first index. Worst-case complexity is O(n) where the element is found at the last index or element is not present in the array.09-Feb-2021,
Example of Linear Search Algorithm Step 1: The searched element 39 is compared to the first element of an array, which is 13. The match is not found, you now move on to the next element and try to implement a comparison. Step 2: Now, search element 39 is compared to the second element of an array, 9.21-Feb-2022
The Big O notation for Linear Search is O(N). The complexity is directly related to the size of the inputs — the algorithm takes an additional step for each additional data element.21-Mar-2021
Binary search is more efficient than linear search; it has a time complexity of O(log n). The list of data must be in a sorted order for it to work.29-Dec-2017
Best-case performance for algorithm The term best-case performance is used in computer science to describe an algorithm's behavior under optimal conditions. For example, the best case for a simple linear search on a list occurs when the desired element is the first element of the list.
For a list with n items, the best case is when the value is equal to the first element of the list, in which case only one comparison is needed. The worst case is when the value is not in the list (or occurs only once at the end of the list), in which case n comparisons are needed.
Linear Search's best case is when the key is in the first position, making the best case time complexity O(1). While the worst case occurs when the desired element is in the last position. In this case, we need to compare the key with all of the elements in the array, making it O(n) time complexity in the worst case.17-Jul-2020
Explanation: Where the element is not present in the array, ordered linear search is better than unordered, but the best and worst cases remain the same, with the key element being located in the first or last place.26-Apr-2021
Best Case Time Complexity of Linear Search: O(1) Average Case Time Complexity of Linear Search: O(N)