steps involved in the merge sort algorithm.

**Merge Sort** is a divide-and-conquer sorting algorithm that divides a list into smaller sublists, sorts those sublists, and then merges them back together to form a sorted list. Here are the steps involved in the merge sort algorithm:

1. **Divide**:

   - **Step**: Split the unsorted list into two approximately equal halves.

   - **Base Case**: If the list has one or zero elements, it is already sorted and no further action is needed.

2. **Conquer**:

   - **Step**: Recursively apply merge sort to each half of the list. This means each sublist is divided further until they are small enough to be sorted easily (i.e., single-element lists).

3. **Combine**:

   - **Step**: Merge the sorted sublists back together into a single sorted list. This is done by comparing the smallest elements of each sublist and combining them in order.

4. **Merge Process**:

   - **Step**: Take two sorted sublists and merge them into a single sorted list. This is done by repeatedly taking the smallest available element from the front of either sublist and appending it to the merged list until all elements from both sublists are processed.

**Example**:

1. **Original List**: `[38, 27, 43, 3, 9, 82, 10]`

2. **Divide**:

   - Split into `[38, 27, 43, 3]` and `[9, 82, 10]`

3. **Conquer**:

   - Split `[38, 27, 43, 3]` into `[38, 27]` and `[43, 3]`

     - Split `[38, 27]` into `[38]` and `[27]` (both are sorted)

     - Merge `[38]` and `[27]` into `[27, 38]`

     - Split `[43, 3]` into `[43]` and `[3]` (both are sorted)

     - Merge `[43]` and `[3]` into `[3, 43]`

     - Merge `[27, 38]` and `[3, 43]` into `[3, 27, 38, 43]`

   - Split `[9, 82, 10]` into `[9]` and `[82, 10]`

     - Split `[82, 10]` into `[82]` and `[10]` (both are sorted)

     - Merge `[82]` and `[10]` into `[10, 82]`

     - Merge `[9]` and `[10, 82]` into `[9, 10, 82]`

4. **Combine**:

   - Merge `[3, 27, 38, 43]` and `[9, 10, 82]` into `[3, 9, 10, 27, 38, 43, 82]`

**Summary**: Merge sort divides the list into smaller parts, sorts those parts, and then merges them back together in a sorted order. This algorithm has a time complexity of O(n log n) and is known for its efficiency and stability.