Teach me about the Merge sorting in the C++ in detail with better visuallze and the steps to do it and make sure the steps are easy to approach

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Merge Sort is a powerful divide-and-conquer sorting algorithm with O(n log n) time complexity. It works by recursively dividing the array into smaller subarrays until each contains only one element, then merging them back together in sorted order. This approach makes it stable and efficient for large datasets. The divide phase recursively splits the array into smaller subarrays. Starting with the original array of seven elements, we first split it into two halves. Then we continue dividing each subarray until we reach the base case where each subarray contains only one element. This creates a tree-like structure with log n levels. The merge process combines two sorted arrays into one sorted array. We use two pointers to track positions in each array and one pointer for the result. We compare elements at current positions, select the smaller one, place it in the result array, and advance the corresponding pointer. This process continues until all elements are merged. The complete merge sort algorithm combines divide and conquer phases. Starting with the original array, we recursively divide it until we have single elements. Then we merge pairs back together in sorted order. The algorithm has O(n log n) time complexity and O(n) space complexity due to the temporary arrays needed for merging. Merge Sort is one of the most efficient and reliable sorting algorithms. It uses a divide-and-conquer strategy where we split the array into smaller pieces, sort each piece, and then merge them back together in the correct order. The algorithm guarantees O(n log n) time complexity in all cases, making it very predictable and suitable for large datasets. The divide phase is the first step of merge sort. We start with the original array and repeatedly split it in half until we have individual elements. Each split creates two smaller subarrays. This process continues recursively, creating a binary tree structure where each leaf represents a single element. The depth of this tree is log n, which is why merge sort has logarithmic complexity. The merge process is where the magic happens. We take two sorted arrays and combine them into one larger sorted array. We use two pointers, one for each array, and compare the elements they point to. We always take the smaller element and add it to the result. This process continues until we've processed all elements from both arrays. Let's see the complete merge sort process in action. Starting with array [64, 34, 25, 12, 22, 11, 90], we first divide it recursively until we have individual elements. Then we merge them back together in sorted order. The final result is [11, 12, 22, 25, 34, 64, 90]. The algorithm maintains O(n log n) time complexity because we have log n levels of recursion, and each level processes n elements during merging. Here's the complete C++ implementation of merge sort. The mergeSort function handles the recursive division, while the merge function combines two sorted subarrays. Key points include using vectors for dynamic memory management, proper index calculations to avoid overflow, and handling remaining elements after one array is exhausted. The algorithm is stable and works efficiently for large datasets.