Rope Data Structure - Problem

A Rope is a binary tree data structure for efficiently storing and manipulating very large strings. Each leaf contains a short string and a weight, and each node contains the sum of the weights of all leaves in its left subtree.

Implement a Rope data structure that supports the following operations:

insert(index, text) - Insert text at the given index
delete(start, end) - Delete characters from start to end (exclusive)
charAt(index) - Get character at the given index
substring(start, end) - Get substring from start to end (exclusive)
length() - Get total length of the rope

For this problem, implement a simplified version that processes a sequence of operations and returns the final string representation.

Input & Output

Example 1 — Basic Insert Operations

$ Input: operations = [["insert", 0, "hello"], ["insert", 5, " world"]]

› Output: "hello world"

💡 Note: Start with empty rope. Insert "hello" at position 0, then insert " world" at position 5 (end of "hello"). Final string is "hello world".

Example 2 — Mixed Operations

$ Input: operations = [["insert", 0, "abc"], ["insert", 1, "XY"], ["charAt", 2]]

› Output: "Y"

💡 Note: Insert "abc" at 0 → "abc". Insert "XY" at position 1 → "aXYbc". Get character at index 2 → "Y".

Example 3 — Delete and Length

$ Input: operations = [["insert", 0, "programming"], ["delete", 3, 7], ["length"]]

› Output: "7"

💡 Note: Insert "programming" → "programming". Delete characters from index 3 to 7 → "proaming" (removed "gr"). Length is 7.

Constraints

1 ≤ operations.length ≤ 1000
0 ≤ index ≤ current string length
1 ≤ text.length ≤ 100
Text contains only lowercase English letters and spaces

Visualization

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Asked in

G Google 25 M Microsoft 20 a Amazon 15 f Facebook 12

The key insight is using a binary tree where leaves contain string fragments and internal nodes store left subtree weights for O(log n) navigation. The Rope data structure enables efficient string operations by avoiding costly character shifting. Best approach: Binary tree with weight annotations. Time: O(log n), Space: O(n)

Common Approaches

✓ Brute Force String Operations

⏱️ Time: O(n) Space: O(n)

Maintain the text as one continuous string/array. For each operation, directly manipulate the string by shifting characters for insertions/deletions and accessing by index for queries.

Rope Data Structure

⏱️ Time: O(log n) Space: O(n)

Implement a binary tree where each leaf contains a string fragment and each internal node stores the total length of all strings in its left subtree. This allows efficient splitting, concatenation, and indexing operations.

Brute Force String Operations — Algorithm Steps

Store text as a single string
For insert: create new string with text inserted
For delete: create new string with characters removed
For charAt: directly access string[index]

Visualization

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Step-by-Step Walkthrough

Initial String

Start with empty or initial string

Insert Operation

Copy prefix + new text + suffix to create new string

Result

Complete string after all operations

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

char* solution(char operations[][100], int opCount) {
    char* text = malloc(10000);
    text[0] = '\0';
    
    for (int i = 0; i < opCount; i++) {
        // Simple parsing - in practice would need full JSON parser
        if (strstr(operations[i], "insert")) {
            // Parse and perform insert
        } else if (strstr(operations[i], "delete")) {
            // Parse and perform delete
        }
        // Handle other operations...
    }
    
    return text;
}

int main() {
    char operations[100][100];
    int opCount = 0;
    
    char* result = solution(operations, opCount);
    printf("%s\n", result);
    free(result);
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(n)

Each insert/delete operation requires creating a new string and copying up to n characters

✓ Linear Growth

Space Complexity

O(n)

Store the entire string as a single array of n characters

⚡ Linearithmic Space

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Rope Data Structure - Problem

Input & Output

Constraints

Visualization

Related Problems

Common Approaches

Brute Force String Operations — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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