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This approach involves repeating the string a
incrementally and checking if b
becomes a substring. The minimum length of repeated a
needed should be at least equal to b
's length. Thus, start by repeating a
just enough times to get a string longer than b
and check if b
is a substring. If not, repeat a
one more time to cover scenarios where b
spans two a
's boundary.
Time Complexity: O((m + n) * n), where m
is the length of a
and n
is the length of b
. Space Complexity: O(m + n).
1function repeatedStringMatch(a, b) {
2 const m = a.length, n = b.length;
3 const repeat = Math.ceil(n / m);
4 let repeatedA = '';
5 for (let i = 0; i <= repeat + 1; i++) {
6 if (repeatedA.includes(b)) return i;
7 repeatedA += a;
8 }
9 return -1;
10}
11
12// Example
13console.log(repeatedStringMatch("abcd", "cdabcdab"));
This JavaScript function repeats string a
and checks if b
is a substring, incrementing the number of repeats until it finds a match or exhausts logical possibilities.
This approach relies on two repeated concatenations of string a
. As per the pigeonhole principle, if b
can fit within the repeated strings, it should certainly fit within two full concatenated repetitions and its prefix or suffix match.
Time Complexity: O(m * n). Space Complexity: O(m).
1
public class Solution {
public int RepeatedStringMatch(string a, string b) {
int m = a.Length, n = b.Length;
int repeatMax = (n + m - 1) / m;
string doubled = a + a;
for (int i = 0; i <= repeatMax; i++) {
if ((doubled + a).Substring(i).Contains(b))
return i + 1;
}
return -1;
}
public static void Main(string[] args) {
Solution solution = new Solution();
Console.WriteLine(solution.RepeatedStringMatch("abcd", "cdabcdab"));
}
}
This C# code cleverly manages string assembly using a block information strategy, quickly searching a bounded area formed by two repetitions of a.