COMPUTER SCIENCE AND ENGINEERING
ALGORITHMS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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O(n)
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O(n2)
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O(n3)
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All will execute in same time.
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Detailed explanation-1: -The time complexity increases with the increase in the term ‘n’. The same can be seen in the above-given algorithm complexities, the largest value of ‘n’ is in the third multiple of n. So, the slowest execution of the algorithm will be for the O(n³).
Detailed explanation-2: -The Correct option they are mentioning is O(logN).
Detailed explanation-3: -O(N²)-Quadratic O(N²) represents the complexity of an algorithm, whose performance is proportional to the square of the size of the input elements. It is generally quite slow: If the input array has 1 element it will do 1 operation, if it has 10 elements it will do 100 operations, and so on.
Detailed explanation-4: -O(2n) An example of an O(2n) function is the recursive calculation of Fibonacci numbers. O(2n) denotes an algorithm whose growth doubles with each addition to the input data set.
Detailed explanation-5: -Constant Time Complexity: O(1) When an algorithm has constant time with order O (1) and is independent of the input size n, it is said to have constant time with order O (1).