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(2n)
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O(log n)
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O(n2)
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O(1)
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Detailed explanation-1: -The Divide and Conquer algorithm solves the problem in O(nLogn) time. Strassen’s Algorithm is an efficient algorithm to multiply two matrices. A simple method to multiply two matrices need 3 nested loops and is O(n^3) .
Detailed explanation-2: -Nlogn Defined O(nlogn), also known as loglinear complexity, implies that logn operations will occur n times. It’s commonly used in recursive sorting algorithms and binary tree sorting algorithms. Space complexities of O(nlogn) are extremely rare to the point that you don’t need to keep an eye out for it.
Detailed explanation-3: -O(log N) is a common runtime complexity. Examples include binary searches, finding the smallest or largest value in a binary search tree, and certain divide and conquer algorithms. If an algorithm is dividing the elements being considered by 2 each iteration, then it likely has a runtime complexity of O(log N).
Detailed explanation-4: -No, divide and conquer doesn’t guarantee O(nlogn) performance. It all depends on how the problem gets simplified on each recursion. In the merge sort algorithm, the original problem is divided into two halves. Then an O(n) operation is performed on the results.