Final Array State After K Multiplication Operations I | Detailed | Leetcode 3264 | codestorywithMIK
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This is the 60th Video of our Playlist "Leetcode Easy" by codestorywithMIK
In this video we will try to solve an easy problem based on heap : Final Array State After K Multiplication Operations I | Something New To Learn | Leetcode 3264 | codestorywithMIK
I will explain the intuition so easily that you will never forget and start seeing this as cakewalk EASYYY.
We will do live coding after explanation and see if we are able to pass all the test cases.
Also, please note that my Github solution link below contains both C++ as well as JAVA code.
Problem Name : Final Array State After K Multiplication Operations I | Something New To Learn | Leetcode 3264 | codestorywithMIK
Company Tags : will update later
My solutions on Github(C++ & JAVA) - https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/Heap/Leetcode Easy/Final Array State After K Multiplication Operations I.cpp
Leetcode Link : https://leetcode.com/problems/final-array-state-after-k-multiplication-operations-i
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Summary :
Approach-1 (Brute Force)
Description: This approach iteratively scans the entire array to find the smallest element in each of the k iterations. Once found, the smallest element is multiplied by the given multiplier. This method directly modifies the input array without using additional data structures.
Approach-2 (Using priority_queue)
Description: This approach uses a min-heap (priority_queue) to efficiently track the smallest element. Initially, all elements are added to the heap. In each iteration, the smallest element is extracted, updated by multiplying it with the multiplier, and then reinserted into the heap. This allows for efficient management of the smallest element.
Approach-3 (Using vector as heap for O(n) heapify)
Description: The array is converted into a heap using make_heap, which organizes the elements efficiently in heap order. In each of the k iterations, the smallest element is extracted using pop_heap, updated by multiplying it with the multiplier, and then reinserted using push_heap. This approach leverages the vector container and heap utilities to manage the heap structure efficiently.
Note: This approach cannot be implemented in Java because Java does not provide library functions like make_heap, push_heap, or pop_heap.
✨ Timelines✨
00:00 - Introduction
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