The big-O time efficiency for performing Binary search for an item in a sorted list is: O(1) O(log(n)) O(n) O(nlog(n))
The big-O time efficiency for performing Binary search for an item in a sorted list is:
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O(1) |
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O(log(n)) |
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O(n) |
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O(nlog(n)) |
Binary search is an efficient algorithm for searching an elements from a sorted list of items. It works on the principle of divide and conquer. In this approach, repeatedly dividing the search interval in half of the list so the element is always searched in the middle of list. In each iteration it divide the list into two parts then compare the mid element with searching element. If the mid element is smaller than search element then we search in second part of list otherwise search in first part of list.
For example:
step1. If list is [2,5,6,9,13,15,28,30] and search element is 30 //=>mid value is: 9 target is : 30
step2. [13,15,28,30] //=> mid value is: 15 target is : 30
step3. [28,30] // => mid value is: 28 target is : 30
step4. [30] //=> mid value is: 30 target is : 30
Binary search is a fast search algorithm with run-time complexity of Ο(log n).
Here n=8, therefore, O(log 8) = O(log223) = O(3), i.e. we need 3 steps.
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