Remove Zero Sum Consecutive Nodes from Linked List

Data Structures
Medium
Amazon
82.1K views

Given the head of a linked list, repeatedly delete consecutive sequences of nodes that sum to 0 until there are no such sequences. Use a Hash Map to track cumulative sums.

Why Interviewers Ask This

Amazon asks this question to evaluate a candidate's mastery of prefix sums and hash map utilization for optimizing linked list traversals. It tests the ability to identify redundant computations and solve complex in-place manipulation problems with O(N) time complexity, reflecting their leadership principle of 'Insist on the Highest Standards' through algorithmic efficiency.

How to Answer This Question

1. Clarify the problem constraints: confirm if the list can be modified in-place or if a new list is required, and verify edge cases like null heads or lists containing only zeros. 2. Propose the optimal strategy: Explain that a brute-force approach checking every subarray is O(N^2), but using a cumulative sum hash map allows us to detect zero-sum sequences in a single pass. 3. Detail the two-pass logic: Describe how the first pass populates the map with running sums and nodes, while the second pass reconstructs the list by skipping nodes between duplicate sums. 4. Discuss space-time trade-offs: Explicitly state the O(N) time and O(N) space complexity, noting why this is acceptable for Amazon's scale. 5. Walk through a dry run: Use a concrete example like [1, -1, 3] to demonstrate how the cumulative sum resets and how pointers are adjusted to remove the sequence.

Key Points to Cover

  • Explicitly mention the O(N) time complexity requirement expected by Amazon engineers
  • Demonstrate understanding of how cumulative sums mathematically prove a zero-sum subarray
  • Address the specific challenge of modifying the linked list structure during traversal
  • Propose a dummy head node to simplify edge case handling for head removal
  • Explain the logic clearly rather than just writing code, showing architectural thinking

Sample Answer

To solve this efficiently, I would leverage the concept of prefix sums combined with a hash map to achieve O(N) time complexity. The core insight is that if we encounter the same cumulative sum at two different nodes, the sequence of nodes between them must sum to zero. First, I would create a dummy node pointing to the head to handle edge cases where the head itself is part of a zero-sum sequence. Then, I would iterate through the list once, maintaining a running cumulative sum. For each node, I would store the mapping from the current cumulative sum to that node in a hash map. If we encounter a sum that already exists in our map, it indicates a zero-sum subarray between the previous occurrence and the current node. However, since we need to remove these nodes, a standard one-pass deletion is tricky because removing nodes affects future sums. Therefore, I prefer a two-pass approach. In the first pass, we populate the map with all cumulative sums and their corresponding nodes. In the second pass, we traverse again; whenever we see a cumulative sum that has been seen before, we update the next pointer of the previous node to skip directly to the node after the current one, effectively deleting the zero-sum segment. This ensures we handle nested or overlapping zero-sum sequences correctly without re-scanning the list repeatedly.

Common Mistakes to Avoid

  • Attempting a brute-force O(N^2) solution by checking every possible subarray, which fails performance standards
  • Failing to use a dummy node, leading to complex pointer logic when the head of the list needs to be removed
  • Not considering that removing a zero-sum sequence might create a new zero-sum sequence requiring iteration
  • Confusing the hash map key as the node value instead of the cumulative running sum

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