← Verkada Inc. Interview Insights
The naive approach is to just copy everything over and sort it, but they explicitly said O(1) space so that kills anything allocation-heavy.
Clarify that the first array has enough capacity and that we need to merge in-place with O(1) extra space. Then propose a three-pointer technique starting from the end of both arrays to avoid overwriting elements, and walk through the algorithm with an example.
Pro tip: Emphasize that merging from the end is the key to achieving O(1) space, and mention that this approach is optimal because it avoids shifting elements. Also, discuss edge cases like one array being empty or all elements of one array being larger than the other.
Confirm that the first array has extra capacity to hold all elements, and that we must merge in-place with O(1) extra space. Clarify that both arrays are sorted in non-decreasing order.
Decide to merge from the end of both arrays to avoid overwriting elements. Use three pointers: one for the last valid element of the first array, one for the last element of the second array, and one for the last position of the merged array.
Compare elements at the two pointers, place the larger one at the write pointer, and move the corresponding pointer and write pointer backward. Continue until all elements from the second array are placed.
Discuss cases where one array is empty, or all elements of one array are larger. State that time complexity is O(m+n) and space complexity is O(1).
Provide a concrete example, such as nums1 = [1,2,3,0,0,0], m=3, nums2 = [2,5,6], n=3, and show step-by-step how the merged array becomes [1,2,2,3,5,6].
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.