How do you solve Split Linked List in Parts on LeetCode?

Split Linked List in Parts (LeetCode #725) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Understanding how to evenly distribute nodes is crucial for solving this problem.

What is the time complexity of Split Linked List in Parts?

The optimal solution for Split Linked List in Parts runs in O(n) time and uses O(n) space. The complexity is O(n) because we traverse the linked list twice: once to count nodes and once to split them into parts.

What is the brute force solution for Split Linked List in Parts?

The brute force approach for Split Linked List in Parts is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute-force approach involves traversing the linked list multiple times to create each part. We can repeatedly extract nodes until we reach the desired number of parts, but this is inefficient. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Split Linked List in Parts?

Split Linked List in Parts uses the following concepts: Linked List. The recommended patterns to study are: Two Pointers, Array.

What are the interview tips for Split Linked List in Parts?

Always clarify edge cases with the interviewer, such as when the list is empty or k is larger than the number of nodes. Explain your thought process as you work through the problem to demonstrate your understanding. Consider both time and space complexity when discussing your solution.

What are common mistakes when solving Split Linked List in Parts?

Failing to account for extra nodes when k is greater than the number of nodes. Not properly handling the null termination of the linked list parts.

#725

Split Linked List in Parts

Medium

Linked ListTwo PointersArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

💡

Intuition

Time O(n)Space O(n)

The optimal solution calculates the size of each part based on the total number of nodes and distributes them evenly. This approach only traverses the list once, making it efficient.

⚙️

Algorithm

3 steps

1Step 1: Calculate the total number of nodes in the linked list.
2Step 2: Determine the size of each part and how many parts should have an extra node.
3Step 3: Traverse the list again, creating each part based on the calculated sizes.

solution.py27 lines

1# Full working Python code
2class ListNode:
3    def __init__(self, val=0, next=None):
4        self.val = val
5        self.next = next
6
7def splitListToParts(head, k):
8    total_nodes = 0
9    current = head
10    while current:
11        total_nodes += 1
12        current = current.next
13    part_size = total_nodes // k
14    extra_parts = total_nodes % k
15    parts = []
16    current = head
17    for i in range(k):
18        parts.append(current)
19        size = part_size + (1 if i < extra_parts else 0)
20        for j in range(size - 1):
21            if current:
22                current = current.next
23        if current:
24            next_part = current.next
25            current.next = None
26            current = next_part
27    return parts

ℹ

Complexity note: The complexity is O(n) because we traverse the linked list twice: once to count nodes and once to split them into parts.

1Understanding how to evenly distribute nodes is crucial for solving this problem.
2Recognizing the need to handle cases where k is greater than the number of nodes helps in preventing errors.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.