Leetcode Merge K Sorted Lists In 2023: A Comprehensive Guide

Merge k Sorted Lists (LeetCode) Visualizations & C++ YouTube
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Introduction

Leetcode is a popular platform for coding enthusiasts who love to solve complex programming problems. One of the most challenging problems on Leetcode is merging k sorted lists. In this article, we will discuss how to solve this problem step-by-step.

What is Merge K Sorted Lists?

Merge k sorted lists is a Leetcode problem that requires us to merge k sorted linked lists into a single sorted list. Each linked list can have a variable number of nodes, and the nodes in each list are already sorted in ascending order.

Why is Merge K Sorted Lists Challenging?

Merging two sorted lists is relatively easy, but merging k sorted lists is much more challenging. This is because we have to compare k nodes at a time to find the smallest node and add it to the merged list. Moreover, we have to repeat this process until all the nodes are merged.

Approaches to Solve Merge K Sorted Lists

There are several approaches to solve the merge k sorted lists problem. In this article, we will discuss two of the most popular approaches: the divide-and-conquer approach and the heap approach.

The Divide-and-Conquer Approach

The divide-and-conquer approach involves dividing the k lists into two halves until we have only two lists left. We can then merge these two lists using a simple merge algorithm. We repeat this process until we have merged all the lists.

The Heap Approach

The heap approach involves using a heap data structure to keep track of the k nodes that we need to compare. We can then add the smallest node to the merged list and replace it with the next node from the same list. We repeat this process until all the nodes are merged.

Implementation

Let’s discuss how to implement the divide-and-conquer approach in Python: “` def mergeKLists(lists: List[ListNode]) -> ListNode: if not lists: return None if len(lists) == 1: return lists[0] mid = len(lists) // 2 left = mergeKLists(lists[:mid]) right = mergeKLists(lists[mid:]) return merge(left, right) def merge(l1: ListNode, l2: ListNode) -> ListNode: if not l1 or not l2: return l1 or l2 if l1.val < l2.val: l1.next = merge(l1.next, l2) return l1 else: l2.next = merge(l1, l2.next) return l2 ``` And here's how to implement the heap approach in Python using the heapq module: ``` import heapq def mergeKLists(lists: List[ListNode]) -> ListNode: heap = [] for i, lst in enumerate(lists): if lst: heapq.heappush(heap, (lst.val, i, lst)) dummy = ListNode(0) curr = dummy while heap: _, i, node = heapq.heappop(heap) curr.next = node curr = curr.next if node.next: heapq.heappush(heap, (node.next.val, i, node.next)) return dummy.next “`

Conclusion

In this article, we have discussed how to solve the merge k sorted lists problem on Leetcode using two popular approaches: the divide-and-conquer approach and the heap approach. We have also provided Python implementations of both approaches. By understanding these approaches, you can improve your problem-solving skills and prepare yourself for more challenging coding problems.

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