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 ith letter is distance[i]. If the ith letter does not appear in s, then distance[i] can be ignored.

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

Example 1:

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
Explanation:
- 'a' appears at indices 0 and 2 so it satisfies distance[0] = 1.
- 'b' appears at indices 1 and 5 so it satisfies distance[1] = 3.
- 'c' appears at indices 3 and 4 so it satisfies distance[2] = 0.
Note that distance[3] = 5, but since 'd' does not appear in s, it can be ignored.
Return true because s is a well-spaced string.

Example 2:

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
Explanation:
- 'a' appears at indices 0 and 1 so there are zero letters between them.
Because distance[0] = 1, s is not a well-spaced string.

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

Solution (Java)

class Solution {
    public boolean checkDistances(String s, int[] distance) {

        boolean valid = true;

        HashMap<Character,Integer> map = new HashMap<>();
        int n = s.length();

        // System.out.println('c'-'a');

        for(int i = 0 ; i < n ; i++){

            char c = s.charAt(i);
            if(map.containsKey(c)){
                int value = i - map.get(c) - 1;
                if(value != distance[c-'a'])return false;
            }else{
                map.put(c,i);
            }
        }

        return valid;
    }
}

Explain:

nope.

Complexity:

Time complexity : O(n).
Space complexity : O(n).