Replit·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026Remote

Summary

Replit SWE interview with a pretty involved coding problem around simulating a text editor's keystroke compression. The problem itself was well-designed but I spent way too long on edge cases and not enough time on the core logic upfront.

Questions Asked (1)

You're given an initial document string and a sequence of keystroke operations (append a character, backspace, or move cursor right). Convert this sequence into a compressed list of higher-level operations: insert a string, delete k characters, or skip k positions. Consecutive same-type operations should be merged, and redundant sequences like appending then immediately deleting should cancel out.

Algorithms & Data StructuresTechnical Trade-offsSystem Design

Author's notes

This one took me a while to frame correctly.

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AI HintsAI Generated

Suggested Approach

Clarify the exact semantics of each keystroke and the desired output format, then design a single-pass algorithm that processes operations while maintaining a cursor position and a stack of compressed operations. Use a stack to merge consecutive same-type operations and cancel redundant pairs like append-then-backspace, ensuring O(n) time and space.

Pro tip: Explicitly discuss how you handle edge cases such as backspacing at the beginning of the document or moving the cursor beyond the current text length, and explain how your merging logic preserves correctness when operations are interleaved.

1. Clarify requirements and edge cases

Ask questions to confirm the exact behavior of each keystroke (e.g., does backspace delete the character before the cursor? Can the cursor move beyond the text?) and the expected output format (e.g., list of operations with types and values).

2. Design the data structures

Choose a stack to store compressed operations and a variable to track the cursor position. Each stack element represents an operation (insert, delete, skip) with its value and possibly the cursor position at the time of operation.

3. Process keystrokes and merge operations

Iterate through the keystroke sequence, updating the cursor and the stack. When adding a new operation, check if it can be merged with the top of the stack (same type) or if it cancels a previous operation (e.g., append then backspace).

4. Handle cancellation and redundancy

Implement logic to cancel out redundant sequences: if an append is immediately followed by a backspace, remove the append; if a delete is followed by an insert that restores the deleted text, consider merging or canceling. Also handle cursor movements that may affect operation grouping.

5. Analyze complexity and test

Explain that the algorithm runs in O(n) time and uses O(n) space in the worst case. Walk through a few examples, including edge cases, to demonstrate correctness and discuss potential optimizations.

Key Points to Mention

Cursor position tracking and how it affects operation merging
Stack-based approach for merging consecutive same-type operations
Cancellation of redundant operations (e.g., append followed by backspace)
Handling edge cases: backspace at start, cursor beyond text, empty document
Time and space complexity analysis (O(n) time, O(n) space)
Trade-offs between different merging strategies (e.g., eager vs. lazy merging)

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