Consider the following variation on MergeSort: instead of dividing a list (say, of integers) evenly (thatis, half and half or half and half plus 1) at all levels of recursion, we choose to divide a list this way- a left list that consists of exactly one integer and a right list that consists of the remaining integers.The time-complexity of this variation of MergeSort is:(a) O(n log n)(b) O(n²)(c) O(n)(d) none of the above

Merge sort is a popular sorting algorithm that follows the divide-and-conquer paradigm. It divides…

Answered: Consider the following variation on…

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Merge sort is an efficient sorting algorithm with a time complexity of O(n log n). This means that as the number of elements (chocolates or students) increases significantly, the efficiency of merge sort remains relatively stable compared to other sorting algorithms. Merge sort achieves this efficiency by recursively dividing the input array into smaller sub-arrays, sorting them individually, and then merging them back together. The efficiency of merge sort is primarily determined by its time complexity, which is , where n is the number of elements in the array. This time complexity indicates that the time taken by merge sort grows logarithmically with the size of the input array. Therefore, even as the number of chocolates or students increases significantly, merge sort maintains its relatively efficient performance. Regarding the distribution of a given set of x to y using iterative and recursive functions, the complexity analysis depends on the specific implementation of each…
Apply quicksort to sort the list E, X, E, R, C, I, S, E in alphabetical order.Draw the tree of the recursive calls made.
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Use Binary Search, Recursive (Algorithm 2.1) to search for the integer 120 in the following list (array) of integers. Show the actions (execution) step by step. No code needed. Solution: 12 34 37 45 57 82 99 120 134 1. Compute the middle index from initial low (1) and high (9) indices: mid = Continue... A