LeetCode 82: Remove Duplicates from Sorted List II — Python Solution

LeetCode 82: Remove Duplicates from Sorted List II is a Medium linked list problem. This Python walkthrough develops a run skipping solution, ties every code decision to a concrete invariant, and includes the regression check used before publication.

This independent guide paraphrases the task rather than reproducing LeetCode’s prompt. Use the official page for the exact statement, examples, constraints, and submission runner.

Recognizing the pattern

Linked-list solutions depend on preserving reachability while rewiring a constant number of pointers. Dummy nodes remove many head-only special cases.

For this problem specifically, use a dummy predecessor. When equal adjacent values begin a duplicate run, skip the entire run; otherwise advance normally. The invariant worth writing beside the code is: The list before prev contains only values that appeared exactly once in processed input.

Step-by-step algorithm

1. Identify the input state consumed by deleteDuplicates(head) and initialize the data required by the run skipping pattern.
2. Use a dummy predecessor. When equal adjacent values begin a duplicate run, skip the entire run; otherwise advance normally.
3. After each update, verify the page’s central invariant: The list before prev contains only values that appeared exactly once in processed input.
4. Finish only after the boundary behavior is covered: Duplicate runs may appear at the head or tail.

Python solution

LeetCode supplies the list, tree, or graph node class referenced by this method. The downloadable test suite includes compatible local node definitions so the implementation can also run outside the judge.

class Solution:
    def deleteDuplicates(self, head):
        dummy = ListNode(0, head)
        previous = dummy
        while head:
            if head.next and head.val == head.next.val:
                duplicate = head.val
                while head and head.val == duplicate:
                    head = head.next
                previous.next = head
            else:
                previous, head = head, head.next
        return dummy.next

Reading the implementation

The main entry point is deleteDuplicates(head). The named working state includes dummy, previous, duplicate, head; those variables make the run skipping state visible instead of hiding it in incidental control flow.

The implementation uses 2 loops with separate responsibilities, so preprocessing and the main traversal can each stay linear in their own input. In concrete terms, use a dummy predecessor. When equal adjacent values begin a duplicate run, skip the entire run; otherwise advance normally.

Correctness argument

Initialization. The data structure starts with exactly the information known before any input element is processed.

Preservation. Use a dummy predecessor. When equal adjacent values begin a duplicate run, skip the entire run; otherwise advance normally. Each update records the current item without invalidating earlier decisions; consequently, the list before prev contains only values that appeared exactly once in processed input.

Termination. The traversal consumes a finite input or finite state space. At the end, the invariant covers the complete input, which is precisely the condition required for the returned result.

Complexity and trade-offs

O(n) time and O(1) extra space. The auxiliary-space figure excludes the returned output unless the output itself is the structure being built.

Copying values into an array makes indexing easy but abandons the intended pointer-space constraint and node identity. That comparison is useful in an interview because it explains why the final implementation is preferable, not merely that it passes.

Regression check

The published implementation belongs to a 100-problem suite that is compiled and exercised behaviorally before deployment.

One reference assertion from that suite is shown below. It targets the normal path while the edge conditions in the next section cover the failure-prone boundaries.

assert listed(Solution().deleteDuplicates(linked([1,2,3,3,4,4,5]))) == [1,2,5]

Common mistakes and edge cases

• Problem-specific boundary: Duplicate runs may appear at the head or tail.
• Pattern-level pitfall: Save the next node before changing a link, terminate reused tails, and check whether the original head can be removed.
• Invariant check: after every update, confirm that the list before prev contains only values that appeared exactly once in processed input.

Interview review checklist

• Explain why run skipping matches the structure of this input.
• State the invariant in one sentence before tracing code: The list before prev contains only values that appeared exactly once in processed input.
• Derive O(n) time and O(1) extra space from how many times each element or state is visited.
• Test the boundary explicitly: Duplicate runs may appear at the head or tail.

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