COMPUTER SCIENCE AND ENGINEERING
ALGORITHMS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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O(log n)
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O(n)
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O(nlog n)
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O(n!)
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Detailed explanation-1: -Big-O means “is of the same order as”. The corresponding little-o means “is ul-timately smaller than”: f (n) = o(1) means that f (n)/c !
Detailed explanation-2: -Big O Notation is a tool used to describe the time complexity of algorithms. It calculates the time taken to run an algorithm as the input grows. In other words, it calculates the worst-case time complexity of an algorithm. Big O Notation in Data Structure describes the upper bound of an algorithm’s runtime.
Detailed explanation-3: -Big O notation-Upper bound, so if a code has conditionals where either of the conditional branches might grow with input size n, then we assume max or upper bound to calculate the time consumption by the code, hence we use Big O for such conditionals assuming we take the path that has max time consumption.
Detailed explanation-4: -What is Big O? Big O, also known as Big O notation, represents an algorithm’s worst-case complexity. It uses algebraic terms to describe the complexity of an algorithm. Big O defines the runtime required to execute an algorithm by identifying how the performance of your algorithm will change as the input size grows.