LeetCode #2296 — HARD

Design a Text Editor

Break down a hard problem into reliable checkpoints, edge-case handling, and complexity trade-offs.

Solve on LeetCode
The Problem

Problem Statement

Design a text editor with a cursor that can do the following:

  • Add text to where the cursor is.
  • Delete text from where the cursor is (simulating the backspace key).
  • Move the cursor either left or right.

When deleting text, only characters to the left of the cursor will be deleted. The cursor will also remain within the actual text and cannot be moved beyond it. More formally, we have that 0 <= cursor.position <= currentText.length always holds.

Implement the TextEditor class:

  • TextEditor() Initializes the object with empty text.
  • void addText(string text) Appends text to where the cursor is. The cursor ends to the right of text.
  • int deleteText(int k) Deletes k characters to the left of the cursor. Returns the number of characters actually deleted.
  • string cursorLeft(int k) Moves the cursor to the left k times. Returns the last min(10, len) characters to the left of the cursor, where len is the number of characters to the left of the cursor.
  • string cursorRight(int k) Moves the cursor to the right k times. Returns the last min(10, len) characters to the left of the cursor, where len is the number of characters to the left of the cursor.

Example 1:

Input
["TextEditor", "addText", "deleteText", "addText", "cursorRight", "cursorLeft", "deleteText", "cursorLeft", "cursorRight"]
[[], ["leetcode"], [4], ["practice"], [3], [8], [10], [2], [6]]
Output
[null, null, 4, null, "etpractice", "leet", 4, "", "practi"]

Explanation
TextEditor textEditor = new TextEditor(); // The current text is "|". (The '|' character represents the cursor)
textEditor.addText("leetcode"); // The current text is "leetcode|".
textEditor.deleteText(4); // return 4
                          // The current text is "leet|". 
                          // 4 characters were deleted.
textEditor.addText("practice"); // The current text is "leetpractice|". 
textEditor.cursorRight(3); // return "etpractice"
                           // The current text is "leetpractice|". 
                           // The cursor cannot be moved beyond the actual text and thus did not move.
                           // "etpractice" is the last 10 characters to the left of the cursor.
textEditor.cursorLeft(8); // return "leet"
                          // The current text is "leet|practice".
                          // "leet" is the last min(10, 4) = 4 characters to the left of the cursor.
textEditor.deleteText(10); // return 4
                           // The current text is "|practice".
                           // Only 4 characters were deleted.
textEditor.cursorLeft(2); // return ""
                          // The current text is "|practice".
                          // The cursor cannot be moved beyond the actual text and thus did not move. 
                          // "" is the last min(10, 0) = 0 characters to the left of the cursor.
textEditor.cursorRight(6); // return "practi"
                           // The current text is "practi|ce".
                           // "practi" is the last min(10, 6) = 6 characters to the left of the cursor.

Constraints:

  • 1 <= text.length, k <= 40
  • text consists of lowercase English letters.
  • At most 2 * 104 calls in total will be made to addText, deleteText, cursorLeft and cursorRight.

Follow-up: Could you find a solution with time complexity of O(k) per call?

Patterns Used

Roadmap

  1. Brute Force Baseline
  2. Core Insight
  3. Algorithm Walkthrough
  4. Edge Cases
  5. Full Annotated Code
  6. Interactive Study Demo
  7. Complexity Analysis
Step 01

Brute Force Baseline

Problem summary: Design a text editor with a cursor that can do the following: Add text to where the cursor is. Delete text from where the cursor is (simulating the backspace key). Move the cursor either left or right. When deleting text, only characters to the left of the cursor will be deleted. The cursor will also remain within the actual text and cannot be moved beyond it. More formally, we have that 0 <= cursor.position <= currentText.length always holds. Implement the TextEditor class: TextEditor() Initializes the object with empty text. void addText(string text) Appends text to where the cursor is. The cursor ends to the right of text. int deleteText(int k) Deletes k characters to the left of the cursor. Returns the number of characters actually deleted. string cursorLeft(int k) Moves the cursor to the left k times. Returns the last min(10, len) characters to the left of the cursor, where len is

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Linked List · Stack · Design

Example 1

["TextEditor","addText","deleteText","addText","cursorRight","cursorLeft","deleteText","cursorLeft","cursorRight"]
[[],["leetcode"],[4],["practice"],[3],[8],[10],[2],[6]]
Step 02

Core Insight

What unlocks the optimal approach

  • Making changes in the middle of some data structures is generally harder than changing the front/back of the same data structure.
  • Can you partition your data structure (text with cursor) into two parts, such that each part changes only near its ends?
  • Can you think of a data structure that supports efficient removals/additions to the front/back?
  • Try to solve the problem with two deques by maintaining the prefix and the suffix separately.
Interview move: turn each hint into an invariant you can check after every iteration/recursion step.
Step 03

Algorithm Walkthrough

Iteration Checklist

  1. Define state (indices, window, stack, map, DP cell, or recursion frame).
  2. Apply one transition step and update the invariant.
  3. Record answer candidate when condition is met.
  4. Continue until all input is consumed.
Use the first example testcase as your mental trace to verify each transition.
Step 04

Edge Cases

Minimum Input
Single element / shortest valid input
Validate boundary behavior before entering the main loop or recursion.
Duplicates & Repeats
Repeated values / repeated states
Decide whether duplicates should be merged, skipped, or counted explicitly.
Extreme Constraints
Largest constraint values
Re-check complexity target against constraints to avoid time-limit issues.
Invalid / Corner Shape
Empty collections, zeros, or disconnected structures
Handle special-case structure before the core algorithm path.
Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #2296: Design a Text Editor
class TextEditor {
    private StringBuilder left = new StringBuilder();
    private StringBuilder right = new StringBuilder();

    public TextEditor() {
    }

    public void addText(String text) {
        left.append(text);
    }

    public int deleteText(int k) {
        k = Math.min(k, left.length());
        left.setLength(left.length() - k);
        return k;
    }

    public String cursorLeft(int k) {
        k = Math.min(k, left.length());
        for (int i = 0; i < k; ++i) {
            right.append(left.charAt(left.length() - 1));
            left.deleteCharAt(left.length() - 1);
        }
        return left.substring(Math.max(left.length() - 10, 0));
    }

    public String cursorRight(int k) {
        k = Math.min(k, right.length());
        for (int i = 0; i < k; ++i) {
            left.append(right.charAt(right.length() - 1));
            right.deleteCharAt(right.length() - 1);
        }
        return left.substring(Math.max(left.length() - 10, 0));
    }
}

/**
 * Your TextEditor object will be instantiated and called as such:
 * TextEditor obj = new TextEditor();
 * obj.addText(text);
 * int param_2 = obj.deleteText(k);
 * String param_3 = obj.cursorLeft(k);
 * String param_4 = obj.cursorRight(k);
 */
Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Press Step or Run All to begin.
Step 07

Complexity Analysis

Time
O(n)
Space
O(1)

Approach Breakdown

COPY TO ARRAY
O(n) time
O(n) space

Copy all n nodes into an array (O(n) time and space), then use array indexing for random access. Operations like reversal or middle-finding become trivial with indices, but the O(n) extra space defeats the purpose of using a linked list.

IN-PLACE POINTERS
O(n) time
O(1) space

Most linked list operations traverse the list once (O(n)) and re-wire pointers in-place (O(1) extra space). The brute force often copies nodes to an array to enable random access, costing O(n) space. In-place pointer manipulation eliminates that.

Shortcut: Traverse once + re-wire pointers → O(n) time, O(1) space. Dummy head nodes simplify edge cases.
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Losing head/tail while rewiring

Wrong move: Pointer updates overwrite references before they are saved.

Usually fails on: List becomes disconnected mid-operation.

Fix: Store next pointers first and use a dummy head for safer joins.

Breaking monotonic invariant

Wrong move: Pushing without popping stale elements invalidates next-greater/next-smaller logic.

Usually fails on: Indices point to blocked elements and outputs shift.

Fix: Pop while invariant is violated before pushing current element.