Domino and Tromino Tiling
Problem Statement​
Problem Description​
You have two types of tiles: a 2 x 1 domino shape and a tromino shape. You may rotate these shapes.
Given an integer n, return the number of ways to tile a 2 x n board. Since the answer may be very large, return it modulo .
In a tiling, every square must be covered by a tile. Two tilings are different if and only if there are two 4-directionally adjacent cells on the board such that exactly one of the tilings has both squares occupied by a tile.
Examples​
Example 1:
Input: n = 3
Output: 5
Explanation: The five different ways are shown above.
Constraints​
Solution​
Intuition​
To solve this problem, we can use dynamic programming. Let's define dp[i] as the number of ways to tile a 2 x i board. The recurrence relation can be derived based on the ways we can place the last tile(s) on the board.
Time Complexity and Space Complexity Analysis​
- Time Complexity: The solution involves a single loop through the board length 
n, making the time complexity . - Space Complexity: The space complexity is to store the dynamic programming array.
 
Code​
C++​
class Solution {
public:
    int numTilings(int n) {
        if (n == 1) return 1;
        if (n == 2) return 2;
        const int MOD = 1e9 + 7;
        vector<long> dp(n + 1);
        dp[0] = 1;
        dp[1] = 1;
        dp[2] = 2;
        for (int i = 3; i <= n; ++i) {
            dp[i] = (dp[i - 1] + dp[i - 2] + 2 * dp[i - 3]) % MOD;
        }
        return dp[n];
    }
};
Java​
class Solution {
    public int numTilings(int n) {
        if (n == 1) return 1;
        if (n == 2) return 2;
        int MOD = 1000000007;
        long[] dp = new long[n + 1];
        dp[0] = 1;
        dp[1] = 1;
        dp[2] = 2;
        for (int i = 3; i <= n; ++i) {
            dp[i] = (dp[i - 1] + dp[i - 2] + 2 * dp[i - 3]) % MOD;
        }
        return (int) dp[n];
    }
}
Python​
class Solution:
    def numTilings(self, n: int) -> int:
        if n == 1: return 1
        if n == 2: return 2
        MOD = 10**9 + 7
        dp = [0] * (n + 1)
        dp[0] = 1
        dp[1] = 1
        dp[2] = 2
        for i in range(3, n + 1):
            dp[i] = (dp[i - 1] + dp[i - 2] + 2 * dp[i - 3]) % MOD
        return dp[n]