Tip 1: Understand the problem logic, not just the solutions (e.g., arrays, strings, sliding window).
Tip 2: Practice coding trees, linked lists, and HashMaps from scratch.
Tip 3: Build projects using Node.js, JavaScript, and Flask to develop hands-on backend skills.
Tip 1: Make sure you know your projects thoroughly and be honest about them.
Tip 2: Include relevant projects that effectively showcase your skills and experience.



1. If the value is present in the array, return its index.
2. If the value is absent, determine the index where it would be inserted in the array while maintaining the sorted order.
3. The given array has distinct integers.
4. The given array may be empty.
Input: arr = [1, 2, 4, 7], m = 6
Output: 3
Explanation: If the given array 'arr' is: [1, 2, 4, 7] and m = 6. We insert m = 6 in the array and get 'arr' as: [1, 2, 4, 6, 7]. The position of 6 is 3 (according to 0-based indexing)
Step 1: Initialize two pointers, left and right, which represent the start and end indices of the array. Set left = 0 and right = len(nums) - 1.
Step 2: Enter a while loop that runs until left is less than or equal to right. This will allow us to perform a binary search.
Step 3: Calculate the middle index, mid, using the formula mid = left + (right - left) // 2.
Step 4: Compare the element at mid with the target.



Consider the array {2,1,5,6,3,8} and 'K' = 3, the sorted array will be {8, 6, 5, 3, 2, 1}, and the 3rd largest element will be 5.
1) Kth largest element in an array is the kth element of the array when sorted in non-increasing order.
2) All the elements of the array are pairwise distinct.
Step 1: Initialize a min-heap with a capacity of size k. This heap will be used to keep track of the k largest elements encountered so far.
Step 2: Traverse each row of the 2D array, and for each element, do the following:
Step 3: After processing all elements of the 2D array, the root of the heap will hold the kth largest element.

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