Given a linked list, the task is to sort the linked list using the QuickSort algorithm. The function should efficiently rearrange the nodes of the linked list based on their values and return the head of the sorted linked list.
💡 Enhancement / Feature Request (if applicable)
Why It's Useful
Sorting a linked list using QuickSort is beneficial for:
Data Organization: Facilitating efficient access and manipulation of linked list data.
Algorithm Practice: Implementing and understanding sorting algorithms in a data structure context.
Performance Improvement: Offering a more efficient alternative to simple sorting methods, especially for large datasets.
How It Should Work
Partitioning: Implement a partition function to divide the linked list into smaller and larger elements around a pivot.
Recursion: Use recursion to apply QuickSort on the lesser and greater partitions.
Concatenation: Merge the sorted partitions back together to form a single sorted linked list.
🌐 Additional Context
Complexity: The QuickSort algorithm generally has an average time complexity of 𝑂(𝑛log𝑛) and a worst-case complexity of 𝑂(𝑛2) when poorly implemented. However, with proper partitioning, it can be efficient for linked lists.
Edge Cases: Consider handling edge cases such as:
An empty linked list should return None.
A linked list with a single element should return the same node.
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📝 Description
Given a linked list, the task is to sort the linked list using the QuickSort algorithm. The function should efficiently rearrange the nodes of the linked list based on their values and return the head of the sorted linked list.
💡 Enhancement / Feature Request (if applicable)
Why It's Useful Sorting a linked list using QuickSort is beneficial for:
Data Organization: Facilitating efficient access and manipulation of linked list data. Algorithm Practice: Implementing and understanding sorting algorithms in a data structure context. Performance Improvement: Offering a more efficient alternative to simple sorting methods, especially for large datasets. How It Should Work Partitioning: Implement a partition function to divide the linked list into smaller and larger elements around a pivot. Recursion: Use recursion to apply QuickSort on the lesser and greater partitions. Concatenation: Merge the sorted partitions back together to form a single sorted linked list.
🌐 Additional Context
Complexity: The QuickSort algorithm generally has an average time complexity of 𝑂(𝑛log𝑛) and a worst-case complexity of 𝑂(𝑛2) when poorly implemented. However, with proper partitioning, it can be efficient for linked lists.
Edge Cases: Consider handling edge cases such as:
An empty linked list should return None. A linked list with a single element should return the same node.