Count Paths With the Given XOR Value
MediumUpdated: Aug 2, 2025
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Problem
You are given a 2D integer array grid with size m x n. You are also given an integer k.
Your task is to calculate the number of paths you can take from the top-left cell (0, 0) to the bottom-right cell (m - 1, n - 1) satisfying the following constraints :
- You can either move to the right or down. Formally, from the cell
(i, j)you may move to the cell(i, j + 1)or to the cell(i + 1, j)if the target cell exists. - The
XORof all the numbers on the path must be equal tok.
Return the total number of such paths.
Since the answer can be very large, return the result modulo 10^9 + 7.
Examples
Example 1
Input:d = [[2, 1, 5], [7, 10, 0], [12, 6, 4]], k = 11
Output: 3
Explanation:
The 3 paths are:
* `(0, 0) -> (1, 0) -> (2, 0) -> (2, 1) -> (2, 2)`
* `(0, 0) -> (1, 0) -> (1, 1) -> (1, 2) -> (2, 2)`
* `(0, 0) -> (0, 1) -> (1, 1) -> (2, 1) -> (2, 2)`
Example 2
Input:d = [[1, 3, 3, 3], [0, 3, 3, 2], [3, 0, 1, 1]], k = 2
Output: 5
Explanation:
The 5 paths are:
* `(0, 0) -> (1, 0) -> (2, 0) -> (2, 1) -> (2, 2) -> (2, 3)`
* `(0, 0) -> (1, 0) -> (1, 1) -> (2, 1) -> (2, 2) -> (2, 3)`
* `(0, 0) -> (1, 0) -> (1, 1) -> (1, 2) -> (1, 3) -> (2, 3)`
* `(0, 0) -> (0, 1) -> (1, 1) -> (1, 2) -> (2, 2) -> (2, 3)`
* `(0, 0) -> (0, 1) -> (0, 2) -> (1, 2) -> (2, 2) -> (2, 3)`
Example 3
Input:d = [[1, 1, 1, 2], [3, 0, 3, 2], [3, 0, 2, 2]], k = 10
Output: 0
Constraints
1 <= m == grid.length <= 3001 <= n == grid[r].length <= 3000 <= grid[r][c] < 160 <= k < 16
Solution
Method 1 – Dynamic Programming (DP) with XOR State
Intuition
Since the grid values and k are small (0-15), we can use DP to track the number of ways to reach each cell with a given XOR value. For each cell, the number of ways to reach it with XOR x is the sum of the ways to reach the cell above and the cell to the left with XOR (x ^ grid[i][j]).
Approach
- Let
dp[i][j][x]be the number of ways to reach cell (i, j) with XOR value x. - Initialize
dp[0][0][grid[0][0]] = 1. - For each cell (i, j), for each possible XOR value x (0 to 15):
- If i > 0, add
dp[i-1][j][x ^ grid[i][j]]todp[i][j][x]. - If j > 0, add
dp[i][j-1][x ^ grid[i][j]]todp[i][j][x].
- If i > 0, add
- The answer is
dp[m-1][n-1][k]. - Return the answer modulo 10^9+7.
Code
Java
class Solution {
public int numberOfPaths(int[][] grid, int k) {
int m = grid.length, n = grid[0].length, MOD = 1000000007;
int[][][] dp = new int[m][n][16];
dp[0][0][grid[0][0]] = 1;
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
for (int x = 0; x < 16; x++) {
if (i > 0) dp[i][j][x] = (dp[i][j][x] + dp[i-1][j][x ^ grid[i][j]]) % MOD;
if (j > 0) dp[i][j][x] = (dp[i][j][x] + dp[i][j-1][x ^ grid[i][j]]) % MOD;
}
}
}
return dp[m-1][n-1][k];
}
}
Python
class Solution:
def numberOfPaths(self, grid: list[list[int]], k: int) -> int:
m, n = len(grid), len(grid[0])
MOD = 10**9 + 7
dp = [[[0]*16 for _ in range(n)] for _ in range(m)]
dp[0][0][grid[0][0]] = 1
for i in range(m):
for j in range(n):
for x in range(16):
if i > 0:
dp[i][j][x] = (dp[i][j][x] + dp[i-1][j][x ^ grid[i][j]]) % MOD
if j > 0:
dp[i][j][x] = (dp[i][j][x] + dp[i][j-1][x ^ grid[i][j]]) % MOD
return dp[m-1][n-1][k]
Complexity
- ⏰ Time complexity:
O(m * n * 16), since we process each cell and each possible XOR value. - 🧺 Space complexity:
O(m * n * 16), for the DP table.