Check Distances Between Same Letters

Check Distances Between Same Letters - Problem

You are given a 0-indexed string s consisting of only lowercase English letters, where each letter in s appears exactly twice. You are also given a 0-indexed integer array distance of length 26.

Each letter in the alphabet is numbered from 0 to 25 (i.e. 'a' → 0, 'b' → 1, 'c' → 2, ..., 'z' → 25).

In a well-spaced string, the number of letters between the two occurrences of the i^th letter is distance[i]. If the i^th letter does not appear in s, then distance[i] can be ignored.

Return true if s is a well-spaced string, otherwise return false.

Input & Output

Example 1 — Basic Valid Case

$ Input: s = "abaccb", distance = [1,3,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]

› Output: true

💡 Note: Character 'a' appears at positions 0,2 with 1 character between (distance[0]=1 ✓). Character 'b' appears at positions 1,5 with 3 characters between (distance[1]=3 ✓). Character 'c' appears at positions 3,4 with 0 characters between (distance[2]=0 ✓).

Example 2 — Invalid Distance

$ Input: s = "aa", distance = [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]

› Output: false

💡 Note: Character 'a' appears at positions 0,1 with 0 characters between, but distance[0]=1 requires 1 character between them.

Example 3 — Perfect Adjacent Match

$ Input: s = "aa", distance = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]

› Output: true

💡 Note: Character 'a' appears at positions 0,1 with 0 characters between, matching distance[0]=0 exactly.

Constraints

2 ≤ s.length ≤ 52
s consists only of lowercase English letters
Each letter appears in s exactly twice
distance.length == 26
0 ≤ distance[i] ≤ 50

Visualization

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Asked in

G Google 12 f Meta 8 M Microsoft 6

The optimal approach uses a hash map to track first occurrences and validate distances on second occurrences in a single pass. Key insight: Instead of finding all pairs first, validate immediately when encountering the second occurrence of each character. Time: O(n), Space: O(1).

Common Approaches

✓ Brute Force - Find All Pairs

⏱️ Time: O(n²) Space: O(1)

Iterate through each character in the string, find all its occurrences, and verify the distance between the two matches the required distance.

Hash Map - Single Pass

⏱️ Time: O(n) Space: O(1)

Use a hash map to store the first occurrence of each character. When we encounter the same character again, calculate the distance and validate immediately.

Brute Force - Find All Pairs — Algorithm Steps

Step 1: For each character, scan string to find both positions
Step 2: Calculate distance between positions
Step 3: Compare with required distance from array

Visualization

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Step-by-Step Walkthrough

Find First 'a'

Scan from position to find matching character

Calculate Distance

Count characters between the two positions

Validate

Check if distance matches requirement

Code -

solution.c — C

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

bool solution(char* s, int* distance) {
    int n = strlen(s);
    for (int i = 0; i < n; i++) {
        char ch = s[i];
        int charIdx = ch - 'a';
        
        // Find the other occurrence of this character
        for (int j = i + 1; j < n; j++) {
            if (s[j] == ch) {
                // Check if distance matches
                int actualDistance = j - i - 1;
                if (actualDistance != distance[charIdx]) {
                    return false;
                }
                break;
            }
        }
    }
    return true;
}

int main() {
    char s[1000];
    fgets(s, sizeof(s), stdin);
    s[strcspn(s, "\n")] = 0;
    
    char distanceStr[10000];
    fgets(distanceStr, sizeof(distanceStr), stdin);
    
    // Parse array manually
    int distance[26];
    char* token = strtok(distanceStr + 1, ",");
    int idx = 0;
    while (token != NULL && idx < 26) {
        distance[idx++] = atoi(token);
        token = strtok(NULL, ",");
    }
    
    bool result = solution(s, distance);
    printf(result ? "true\n" : "false\n");
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(n²)

For each character position, we scan the entire string to find its pair

⚠ Quadratic Growth

Space Complexity

O(1)

Only using constant extra variables for tracking positions

✓ Linear Space

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Input & Output

Constraints

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Related Problems

Common Approaches

Brute Force - Find All Pairs — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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