Given an array A = [10, 7, 4, 2, 1], and target = 7, return the index of the target if found, else return -1. 1. Can this problem be solved in O(logN)? 2. If so, write the implementation. Mention time and space complexity 3. If this problem cannot be solved using O(logN), what is the solution that you suggest - write the code and also mention time and space complexity.
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Given an array A = [10, 7, 4, 2, 1], and target = 7, return the index of the target if found, else return -1.
1. Can this problem be solved in O(logN)?
2. If so, write the implementation. Mention time and space complexity
3. If this problem cannot be solved using O(logN), what is the solution that you suggest - write the code and also mention time and space complexity.
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- Consider a divide-and-conquer algorithm that calculates the sum of all elements in a set of n numbers by dividing the set into two sets of n/2 numbers each, finding the sum of each of the two subsets recursively, and then adding the result. What is the recurrence relation for the number of operations required for this algorithm? Answer is f(n) = 2 f(n/2) + 1. Please show why this is the case.Given an unsorted array A of integers of any size, n ≥ 3, and an integer value x, write an algorithm as a pseudo code (not a program!) that would find out if there exist EXACTLY3 occurrences in the array with value x. What is the time complexity of your algorithm, in terms of Big-O? What is the space complexity of your algorithm, in terms of Big-O? What if , the given array A is sorted. Will time complexity change from the case that A was unsorted? • If yes; give a new algorithm that achieves this better complexity (indicate the time complexity as of that algorithm). • If no, explain why such new constraints/conditions cannot lead to a better time complexity.You are given an array of integers nums and an integer target. Return the indices of two numbers in the array such that they add up to target. You may assume that each input would have exactly one solution, and you may not use the same element twice. Implement a function in Java to solve this problem using a hash map, and explain the time and space complexity of your solution.
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