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warp·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Coding round for a software engineer role at Warp, focused on a tree data structure problem involving terminal pane splitting. Pretty niche problem, felt like it was testing both OOP design sense and string rendering logic at the same time.

Questions Asked (1)

Q1

Design and implement a PaneTree class that supports splitting terminal panes either vertically or horizontally. Each split should replace a leaf node with an internal node containing the original view and a new view as children. Implement a split(viewId, direction) method and a toString() method that produces a deterministic textual layout of the current pane structure.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

This one took me longer than it should have to get started.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a tree data structure where each node is either a leaf (pane) or an internal node with a direction and two children. Implement split by locating the leaf with the given viewId and replacing it with a new internal node containing the original leaf and a new leaf. For toString, recursively serialize the tree with consistent formatting, ensuring deterministic output by sorting or using a fixed traversal order.

Pro tip: Mention that you would use a recursive approach for both split and toString, and that you'd consider edge cases like splitting a non-existent viewId or handling nested splits. Also, discuss how you might optimize for frequent splits by using a map from viewId to node for O(1) lookup.

1. Clarify requirements and constraints

Ask about the expected input/output format, whether viewIds are unique, and if there are any performance requirements. Confirm that the tree should be binary and that splits are always into two panes.

2. Design the data structure

Define a Node class with type (leaf or internal), viewId (for leaves), direction (for internal), and left/right children. Consider maintaining a map from viewId to node for efficient lookup.

3. Implement split(viewId, direction)

Traverse the tree to find the leaf with viewId. Replace it with an internal node of the given direction, with the original leaf as one child and a new leaf as the other. Update the map accordingly.

4. Implement toString()

Recursively generate a string representation. For leaves, output the viewId; for internal nodes, output the direction and recursively include children, using parentheses or indentation to show structure. Ensure deterministic order (e.g., always left then right).

5. Test and discuss trade-offs

Walk through examples, including nested splits. Discuss time complexity (O(n) for split without map, O(1) with map) and space complexity. Mention potential improvements like balancing or different traversal orders.

Key Points to Mention

  • Tree traversal for finding the leaf to split
  • Maintaining a map from viewId to node for O(1) lookup
  • Recursive implementation for both split and toString
  • Deterministic output by consistent ordering (e.g., left-to-right)
  • Handling edge cases: splitting non-existent viewId, empty tree, or root split
  • Time and space complexity analysis

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