COMPUTER SCIENCE AND ENGINEERING
DATA STRUCTURES
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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O(1)
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O(log n)
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O(n²)
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None of the above
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Detailed explanation-1: -What is Big O Notation in Data Structure? Big O Notation in Data Structure is used to express algorithmic complexity using algebraic terms. It describes the upper bound of an algorithm’s runtime and calculates the time and amount of memory needed to execute the algorithm for an input value.
Detailed explanation-2: -We define input size as the total number of items present in the input. If we increase input size, the total number of operations performed by an algorithm will increase. In other words, time taken by an algorithm will increase with the growth in input size.
Detailed explanation-3: -Time Complexity Consequently, the total computational time is t(N) = c*n, where c is the time consumed for addition of two bits. Here, we observe that t(N) grows linearly as input size increases.
Detailed explanation-4: -Time complexity is the time taken by the algorithm to execute each set of instructions. It is always better to select the most efficient algorithm when a simple problem can solve with different methods. Space complexity is usually referred to as the amount of memory consumed by the algorithm.