# Merge Sort For Linked List

Merge sort is a popular sorting algorithm that is based on the divide-and-conquer technique. It works by dividing an unsorted list into smaller sublists until each sublist consists of only one element, then merging the sublists back together in sorted order. The same basic idea can be applied to linked lists. In this article, we will discuss the implementation of merge sort for linked list.

## Merge Sort for Linked List

The implementation of merge sort for linked lists involves dividing the linked list into two halves, recursively sorting each half, and then merging the two sorted sublists into one sorted linked list. The merge_sort function calls itself recursively until the entire linked list has been sorted.

### Steps to implement Merge Sort for Linked List:

• If the linked list has 0 or 1 element, return it as it is already sorted.
• Divide the linked list into two halves.
• Recursively sort each half of the linked list.
• Merge the two sorted linked lists into a single sorted linked list.

#### 1. Divide the linked list into two halves:

The first step in implementing merge sort for a linked list is to divide the list into two halves. This can be done by using two pointers, a slow pointer, and a fast pointer. The slow pointer moves one step at a time, while the fast pointer moves two steps at a time. When the fast pointer reaches the end of the linked list, the slow pointer will be in the middle of the list.

#### 2. Recursively sort each half:

The second step is to recursively sort each half of the linked list. This is done by dividing each half into two halves until each sublist consists of only one node. At this point, the sublists are considered to be sorted.

#### 3. Merge the sublists:

The third step is to merge the two sorted sublists into one sorted linked list. This is done by comparing the first element of each sublist and adding the smaller element to the new linked list. This process is repeated until all elements have been added to the new linked list.

#### 4. Repeat the process:

The fourth and final step is to repeat the process until the entire linked list has been sorted. This is done by calling the merge sort function recursively on the linked list until it is completely sorted.

### Example

Here is an example of how Merge Sort can be applied to a linked list.

Consider a linked list with the following elements: [7, 5, 3, 2, 8, 6, 4, 1].

1. Divide the linked list into two halves: The linked list is divided into two halves using the get_middle function. The two halves are [7, 5, 3, 2] and [8, 6, 4, 1].

2. Recursively sort each half: The two halves are then recursively sorted using the merge_sort function. The sorted sublists are [2, 3, 5, 7] and [1, 4, 6, 8].

3. Merge the sublists: The two sorted sublists are then merged into one sorted linked list using the merge function. The resulting linked list is [1, 2, 3, 4, 5, 6, 7, 8].

4. Repeat the process: The entire process is repeated until the entire linked list has been sorted.

1. Stable Sorting Algorithm: Merge sort is a stable sorting algorithm that preserves the relative order of equal elements. This is important in certain applications where the order of equal elements must be preserved.

2. Efficient for Linked Lists: Merge sort is particularly well suited for linked lists as it does not require random access to elements, which would require the use of an index. Instead, merge sort can be implemented by splitting the linked list into two parts and recursively sorting each half.

3. O(nlogn) Time Complexity: Merge sort has a time complexity of O(nlogn), which is considered to be efficient for most applications. This makes it suitable for large datasets.

4. Easy to Implement: Merge sort is relatively easy to implement and can be done in a relatively short amount of code. It is also a simple algorithm to understand and debug.

5. High Flexibility: Merge sort is highly flexible and can be adapted to a variety of different data structures, including linked lists, arrays, and binary trees.

6. Scalable: Merge sort can be easily parallelized, making it a scalable algorithm for large datasets.

7. Suitable for External Sorting: Merge sort is also well suited for external sorting, which is the process of sorting data that is too large to fit into memory.

1. High Space Complexity: One of the major disadvantages of merge sort is its high space complexity. It requires additional space to store the sublists that are created during the divide-and-conquer process. This can make it an inefficient sorting algorithm for large datasets with limited memory.

2. Slower than Some Other Sorting Algorithms: Merge sort is slower than some other sorting algorithms, such as quicksort, for smaller datasets. This is because it requires the additional step of dividing the linked list into sublists.

3. Not Cache-Friendly: Merge sort is not cache-friendly, meaning that it does not take advantage of the cache hierarchy in modern computers. This can make it less efficient for datasets that are stored in memory.

4. Recursive Implementation Can be Challenging: The recursive implementation of merge sort can be challenging for some programmers, as it requires a good understanding of recursion and how the divide-and-conquer technique works.

5. Overhead for Merging Process: There is some overhead associated with the merging process in merge sort, as it requires comparisons between elements and the creation of a new sorted linked list. This can make it less efficient than other sorting algorithms for smaller datasets.

Merge sort can be useful when the amount of memory available is limited, as it does not require random access to elements and can be implemented with a linked list data structure. Additionally, merge sort is simple and easy to understand, making it a good choice for educational purposes or when there is a need for an algorithm that is easy to modify.

Overall, Merge Sort is a versatile and efficient sorting algorithm that can be applied to linked lists in a variety of applications.

#### Conclusion

In conclusion, Merge Sort is a powerful sorting algorithm that can be applied to linked lists. It has a time complexity of O(nlogn), making it well-suited for large datasets. Merge sort is also a stable sorting algorithm that preserves the relative order of equal elements. This is important in certain applications where the order of equal elements must be preserved.