Zipline·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jul 2026

Summary

Zipline software engineer interview, got a data structures problem that looked straightforward but had a nasty twist with the popMax operation. Pretty much a pure coding round, no behavioral fluff.

Questions Asked (1)

Design a stack data structure that supports push, pop, top, peekMax, and popMax operations, where popMax removes the maximum value closest to the top if there are duplicates. Discuss the time complexity of each operation.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The push/pop/top part I had down immediately.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and edge cases, then propose a solution using two stacks (one for values, one for maximums) to achieve O(1) for push, pop, top, and peekMax, while popMax requires O(n) in the worst case. Discuss the trade-offs and consider if a more optimized approach (e.g., using a balanced BST or doubly linked list with a max-heap) is warranted, but emphasize the simplicity and efficiency of the two-stack method for most operations.

Pro tip: Mention that the two-stack approach is elegant but popMax is O(n); if the interviewer pushes for optimization, suggest a doubly linked list combined with a TreeMap to achieve O(log n) for all operations, showing you understand advanced data structures.

1. Clarify requirements and edge cases

Ask about the expected frequency of operations, whether the stack can be empty, and how duplicates should be handled. Confirm that popMax removes the maximum value closest to the top.

2. Propose a baseline solution

Describe the two-stack approach: one stack for all elements, another to keep track of the maximum values. Explain how each operation works and its time complexity.

3. Analyze time and space complexity

State that push, pop, top, and peekMax are O(1), while popMax is O(n) in the worst case due to the need to remove an element from the middle of the stack. Space complexity is O(n).

4. Discuss potential optimizations

If required, propose an optimized solution using a doubly linked list and a balanced BST (or TreeMap) to achieve O(log n) for all operations, explaining the trade-offs in complexity and implementation effort.

5. Summarize and conclude

Reiterate the chosen approach, its complexities, and why it fits the problem constraints. Mention any assumptions made.

Key Points to Mention

Two-stack approach for O(1) push, pop, top, and peekMax.
popMax requires O(n) time in the worst case because it may need to remove an element from the middle of the stack.
Handling duplicates: popMax removes the maximum value closest to the top, which the two-stack approach naturally handles if the max stack stores the maximum at each level.
Space complexity is O(n) for the two-stack approach.
Alternative optimized solution using a doubly linked list and a balanced BST (e.g., TreeMap) to achieve O(log n) for all operations.
Trade-offs between simplicity and performance: the two-stack approach is simpler and efficient for most operations, while the optimized approach is more complex but provides better worst-case time for popMax.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.