This took me longer than I expected to get right.
Start by clarifying requirements and edge cases, then propose a data structure (e.g., a gap buffer or piece table) that supports efficient insert/delete and undo/redo. Implement undo/redo using two stacks (undo and redo) that store operations only when they cause a change, and handle delete with k exceeding length by deleting only the available characters.
Pro tip: Mention that undo/redo should store inverse operations or document states, and that only effective operations (those that change the document) should be recorded to avoid no-op undos. Also, discuss the trade-offs between different data structures for text editing.
Ask about expected document size, operation frequency, and whether undo/redo should be unlimited. Clarify that delete with k > length should delete all characters from position i to end, and only if i < length.
Select a data structure for the document (e.g., gap buffer, piece table, or balanced tree) and for undo/redo (two stacks). Explain why the chosen structure balances performance and simplicity.
Define insert, delete, undo, and redo. For delete, compute the effective number of characters to remove (min(k, length - i)) and only push to undo stack if > 0. For undo/redo, pop from one stack, apply inverse, and push to the other.
Write code for the operations, ensuring edge cases like empty document, delete beyond length, and undo/redo with empty stacks are handled. Test with scenarios like multiple undos/redos and interleaved operations.
Talk about time/space complexity, potential optimizations (e.g., batching operations, using persistent data structures), and how the design scales for large documents.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I went with two stacks for undo and redo, which makes push and pop O(1).
Start by listing each editor operation (insert, delete, undo, redo, etc.) and state its time and space complexity. Then explain why you chose specific data structures (e.g., piece table, rope, or gap buffer) by comparing trade-offs and aligning with Notion's real-time collaborative editing needs.
Pro tip: Emphasize that complexity analysis must consider real-world constraints like memory fragmentation and cache locality, not just Big-O. Mention how your choice supports Notion's collaborative features, such as efficient merging of concurrent edits.
List all core editor operations (e.g., insert, delete, undo, redo, search, cursor movement) and any auxiliary operations like serialization or collaboration sync.
For each operation, specify the average and worst-case time and space complexity, using Big-O notation and clarifying assumptions (e.g., document size, edit distribution).
Explain why you chose each data structure (e.g., piece table, rope, gap buffer, balanced tree) by comparing alternatives and highlighting trade-offs in time, space, and implementation complexity.
Relate your choices to Notion's specific needs, such as low-latency editing, real-time collaboration, and memory efficiency for large documents.
Discuss potential bottlenecks or scenarios where your implementation might degrade, and suggest possible optimizations or alternative approaches.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
The 'sequences with no insertions' case tripped me up a bit.
Start by clarifying the undo/redo system's expected behavior and edge cases, then outline a test plan that covers each scenario with clear assertions. For each test, define the initial state, perform operations, and verify the resulting state and stack conditions. Emphasize boundary conditions and error handling.
Pro tip: Demonstrate maturity by discussing how you would structure tests for maintainability and readability, such as using helper functions to set up state and asserting on both the document content and the undo/redo stacks.
Ask questions to confirm the expected behavior of undo/redo, such as whether redo stack clears on new edits and how deletions beyond document length are handled.
For each given scenario, outline the initial state, operations, and expected outcomes, including edge cases like empty document and no-op redo.
Write tests using a consistent pattern: setup, execute, assert. Use descriptive test names and helper functions to reduce duplication.
In each test, assert not only the document content but also the state of undo and redo stacks to ensure correct history management.
Add tests for boundary conditions like deleting more characters than exist, redo with empty stack, and sequences with only deletions.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.