Merge Two Sorted List | LeetCode | CFAM |
Here is the solution for the leetcode problem no 21 Merge Two Sorted List in Python Programming Language.
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Python Code Explanation: Merging Two Sorted Lists Using Linked Lists
In this detailed breakdown, we explore a Python code snippet designed to perform the merge operation on two sorted linked lists efficiently. This code, part of the Solution class, utilizes a pointer-based approach to merge lists while maintaining their sorted order. Understanding both the logic and the computational complexities is crucial for appreciating the efficiency of the implementation.
Linked List Definition
The code begins with the definition of a linked list node:
Each node in the linked list contains a value (val) and a reference to the next node (next), providing the fundamental structure for the input and output of the merging process.
Merge Function:
The core merging logic is encapsulated within the mergeTwoLists method of the Solution class:
Initialization:
head1 and head2 point to the heads of the input lists (l1 and l2).
sorted_list is a dummy node with a value of 0, simplifying the merging logic.
head tracks the head of the merged list and initially points to sorted_list.
Merging Logic:
The central merging process occurs within a while loop:
The loop continues as long as both head1 and head2 have elements.
It compares the values of the current nodes in head1 and head2.
The smaller node is appended to the sorted_list, and the respective pointer (head1 or head2) moves to the next node.
The sorted_list pointer advances to the last added node.
Handling Remaining Elements:
Post-loop, the code checks if either input list is exhausted:
If head1 is None, indicating that all elements from l1 have been processed, the remaining elements from l2 are appended to sorted_list. The reverse case is handled similarly.
Returning the Result:
Finally, the function returns the merged list. As the head pointer was used for convenience, the actual head of the merged list is head. next:
Computational Complexities
Time Complexity: The time complexity of this algorithm is O(n), where n is the total number of nodes in the input lists. The algorithm processes each node once, making it a linear-time solution.
Space Complexity: The space complexity is O(1) since the algorithm uses a constant amount of extra space, regardless of the input size. The space required is independent of the number of nodes in the input lists, making it an efficient in-place solution.
Conclusion
In conclusion, this Python code offers an efficient solution for merging two sorted linked lists with a time complexity of O(n) and a space complexity of O(1). Its use of pointers and a dummy node simplifies the implementation, making it a practical and performant solution for the common task of merging sorted linked lists.
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