Surrounded Regions in Matrix using Graph Traversal
Problem and examples
Given a 2D matrix of size N x M filled with characters 'O' and 'X', the goal is to replace all 'O' cells that are completely surrounded by 'X' on all four sides (up, down, left, right).
'O's that are on the border or connected to a border 'O' should not be changed. Only 'O's that are fully enclosed by 'X' must be replaced.
| Input Matrix | Output Matrix | Description |
|---|---|---|
| [["X", "X", "X", "X"], ["X", "O", "O", "X"], ["X", "X", "O", "X"], ["X", "O", "X", "X"]] | [["X", "X", "X", "X"], ["X", "X", "X", "X"], ["X", "X", "X", "X"], ["X", "O", "X", "X"]] | 'O's at (1,1), (1,2), (2,2) are surrounded, so flipped |
| [["O", "O"], ["O", "O"]] | [["O", "O"], ["O", "O"]] | All 'O's are on border or connected to border, so remain unchanged |
| [["X"]] | [["X"]] | Single cell matrix, no changes |
| [["O"]] | [["O"]] | Single 'O' on border, not flipped |
| [] | [] | Empty matrix, no operation |
| [["X", "X", "X", "X"], ["X", "O", "O", "X"], ["O", "X", "X", "X"], ["X", "O", "X", "O"], ["O", "O", "X", "X"]] | [["X", "X", "X", "X"], ["X", "X", "X", "X"], ["O", "X", "X", "X"], ["X", "O", "X", "O"], ["O", "O", "X", "X"]] | Internal 'O's surrounded and flipped, border-connected 'O's remain |
Explore Surrounded Regions - Graph-Based Matrix Problem
Load an example or enter your own input. Use the player controls to follow each change.
Understanding the Problem
We are given a 2D matrix filled with characters 'X' and 'O'. The goal is to identify and convert all 'O' regions that are completely surrounded by 'X' into 'X's. An 'O' region is defined as a group of connected 'O's (connected horizontally or vertically).
However, if any 'O' in a region is on the border (top row, bottom row, leftmost column, or rightmost column), or is connected to a border 'O', that region is considered safe and should not be converted.
Step-by-Step Solution with Example
Step 1: Identify and understand the input
Let’s take this input matrix:
X X X X
X O O X
X X O X
X O X X
We need to determine which 'O's are surrounded and which are connected to the border.
Step 2: Mark the border-connected 'O's
Start by checking the border cells. If an 'O' is found on the border, perform a BFS/DFS to mark it and all connected 'O's as safe (we can use a temporary marker like '#').
In our example, matrix[3][1] is an 'O' on the border. It is safe. We mark it as '#'. But this 'O' is not connected to any other 'O', so only this cell gets marked.
Step 3: Traverse the matrix to convert unsafe 'O's
Now scan the entire matrix:
- If a cell is
'O', it means it is not connected to any border'O'. It is unsafe and must be converted to'X'. - If a cell is
'#', it was marked safe earlier and should be converted back to'O'.
After this step, our matrix becomes:
X X X X
X X X X
X X X X
X O X X
Step 4: Finalize the matrix
Replace all '#' back to 'O'. Now we have the final matrix with all truly surrounded regions converted and border-connected regions preserved.
Edge Cases
- Empty matrix: No operation needed.
- All 'X's: No changes required.
- All 'O's on border: No 'O' should be changed.
- Matrix with only 1 row or 1 column: All 'O's are border cells and remain unchanged.
Finally
This problem teaches us how to use graph traversal techniques like DFS or BFS to identify connected components, especially under constraints like "not surrounded." Marking safe regions with a temporary symbol is a common trick in matrix-based problems. Always process border-related constraints first and then use a second pass to finalize the result.
- Loop through the border rows and columns of the matrix.
- If an
'O'is found on the border, start a DFS/BFS from there to mark all connected 'O's as'#'. - After marking, traverse the entire matrix:
- If a cell is
'O', change it to'X'. - If a cell is
'#', revert it to'O'.
Implementation and efficiency
C implementation
#include <stdio.h>
#define ROWS 4
#define COLS 4
void dfs(char board[ROWS][COLS], int r, int c) {
if (r < 0 || c < 0 || r >= ROWS || c >= COLS || board[r][c] != 'O') return;
board[r][c] = '#';
dfs(board, r+1, c);
dfs(board, r-1, c);
dfs(board, r, c+1);
dfs(board, r, c-1);
}
void solve(char board[ROWS][COLS]) {
for (int i = 0; i < ROWS; i++) {
if (board[i][0] == 'O') dfs(board, i, 0);
if (board[i][COLS - 1] == 'O') dfs(board, i, COLS - 1);
}
for (int j = 0; j < COLS; j++) {
if (board[0][j] == 'O') dfs(board, 0, j);
if (board[ROWS - 1][j] == 'O') dfs(board, ROWS - 1, j);
}
for (int i = 0; i < ROWS; i++) {
for (int j = 0; j < COLS; j++) {
if (board[i][j] == 'O') board[i][j] = 'X';
if (board[i][j] == '#') board[i][j] = 'O';
}
}
}
int main() {
char board[ROWS][COLS] = {
{'X','X','X','X'},
{'X','O','O','X'},
{'X','X','O','X'},
{'X','O','X','X'}
};
solve(board);
printf("Updated Board:\n");
for (int i = 0; i < ROWS; i++) {
for (int j = 0; j < COLS; j++) {
printf("%c ", board[i][j]);
}
printf("\n");
}
return 0;
}C++ implementation
#include <iostream>
#include <vector>
using namespace std;
void dfs(vector<vector<char>>& board, int r, int c) {
int rows = board.size(), cols = board[0].size();
if (r < 0 || c < 0 || r >= rows || c >= cols || board[r][c] != 'O') return;
board[r][c] = '#';
dfs(board, r+1, c);
dfs(board, r-1, c);
dfs(board, r, c+1);
dfs(board, r, c-1);
}
void solve(vector<vector<char>>& board) {
int rows = board.size(), cols = board[0].size();
for (int i = 0; i < rows; i++) {
if (board[i][0] == 'O') dfs(board, i, 0);
if (board[i][cols - 1] == 'O') dfs(board, i, cols - 1);
}
for (int j = 0; j < cols; j++) {
if (board[0][j] == 'O') dfs(board, 0, j);
if (board[rows - 1][j] == 'O') dfs(board, rows - 1, j);
}
for (int i = 0; i < rows; i++) {
for (int j = 0; j < cols; j++) {
if (board[i][j] == 'O') board[i][j] = 'X';
if (board[i][j] == '#') board[i][j] = 'O';
}
}
}
int main() {
vector<vector<char>> board = {
{'X','X','X','X'},
{'X','O','O','X'},
{'X','X','O','X'},
{'X','O','X','X'}
};
solve(board);
cout << "Updated Board:\n";
for (auto& row : board) {
for (char c : row) cout << c << ' ';
cout << '\n';
}
return 0;
}Python implementation
def dfs(board, r, c):
if r < 0 or c < 0 or r >= len(board) or c >= len(board[0]) or board[r][c] != 'O':
return
board[r][c] = '#'
dfs(board, r+1, c)
dfs(board, r-1, c)
dfs(board, r, c+1)
dfs(board, r, c-1)
def solve(board):
if not board: return
rows, cols = len(board), len(board[0])
for i in range(rows):
if board[i][0] == 'O': dfs(board, i, 0)
if board[i][cols-1] == 'O': dfs(board, i, cols-1)
for j in range(cols):
if board[0][j] == 'O': dfs(board, 0, j)
if board[rows-1][j] == 'O': dfs(board, rows-1, j)
for i in range(rows):
for j in range(cols):
if board[i][j] == 'O': board[i][j] = 'X'
if board[i][j] == '#': board[i][j] = 'O'
board = [
['X','X','X','X'],
['X','O','O','X'],
['X','X','O','X'],
['X','O','X','X']
]
solve(board)
print("Updated Board:")
for row in board:
print(' '.join(row))Java implementation
public class SurroundedRegions {
public static void main(String[] args) {
char[][] board = {
{'X','X','X','X'},
{'X','O','O','X'},
{'X','X','O','X'},
{'X','O','X','X'}
};
solve(board);
System.out.println("Updated Board:");
for (char[] row : board) {
for (char c : row) System.out.print(c + " ");
System.out.println();
}
}
static void dfs(char[][] board, int r, int c) {
int rows = board.length, cols = board[0].length;
if (r < 0 || c < 0 || r >= rows || c >= cols || board[r][c] != 'O') return;
board[r][c] = '#';
dfs(board, r+1, c);
dfs(board, r-1, c);
dfs(board, r, c+1);
dfs(board, r, c-1);
}
static void solve(char[][] board) {
int rows = board.length, cols = board[0].length;
for (int i = 0; i < rows; i++) {
if (board[i][0] == 'O') dfs(board, i, 0);
if (board[i][cols - 1] == 'O') dfs(board, i, cols - 1);
}
for (int j = 0; j < cols; j++) {
if (board[0][j] == 'O') dfs(board, 0, j);
if (board[rows - 1][j] == 'O') dfs(board, rows - 1, j);
}
for (int i = 0; i < rows; i++) {
for (int j = 0; j < cols; j++) {
if (board[i][j] == 'O') board[i][j] = 'X';
if (board[i][j] == '#') board[i][j] = 'O';
}
}
}
}JavaScript implementation
function solve(board) {
const rows = board.length;
if (rows === 0) return;
const cols = board[0].length;
function dfs(r, c) {
if (r < 0 || c < 0 || r >= rows || c >= cols || board[r][c] !== 'O') return;
board[r][c] = '#';
dfs(r + 1, c);
dfs(r - 1, c);
dfs(r, c + 1);
dfs(r, c - 1);
}
for (let i = 0; i < rows; i++) {
if (board[i][0] === 'O') dfs(i, 0);
if (board[i][cols - 1] === 'O') dfs(i, cols - 1);
}
for (let j = 0; j < cols; j++) {
if (board[0][j] === 'O') dfs(0, j);
if (board[rows - 1][j] === 'O') dfs(rows - 1, j);
}
for (let i = 0; i < rows; i++) {
for (let j = 0; j < cols; j++) {
if (board[i][j] === 'O') board[i][j] = 'X';
if (board[i][j] === '#') board[i][j] = 'O';
}
}
return board;
}
const board = [
["X", "X", "X", "X"],
["X", "O", "O", "X"],
["X", "X", "O", "X"],
["X", "O", "X", "X"]
];
console.log("Updated Board:", solve(board));Go implementation
package main
import (
"fmt"
)
func dfs(board [][]byte, r, c int) {
rows, cols := len(board), len(board[0])
if r < 0 || c < 0 || r >= rows || c >= cols || board[r][c] != 'O' {
return
}
board[r][c] = '#'
dfs(board, r+1, c)
dfs(board, r-1, c)
dfs(board, r, c+1)
dfs(board, r, c-1)
}
func solve(board [][]byte) {
rows, cols := len(board), len(board[0])
for i := 0; i < rows; i++ {
if board[i][0] == 'O' {
dfs(board, i, 0)
}
if board[i][cols-1] == 'O' {
dfs(board, i, cols-1)
}
}
for j := 0; j < cols; j++ {
if board[0][j] == 'O' {
dfs(board, 0, j)
}
if board[rows-1][j] == 'O' {
dfs(board, rows-1, j)
}
}
for i := 0; i < rows; i++ {
for j := 0; j < cols; j++ {
if board[i][j] == 'O' {
board[i][j] = 'X'
} else if board[i][j] == '#' {
board[i][j] = 'O'
}
}
}
}
func main() {
board := [][]byte{
{'X','X','X','X'},
{'X','O','O','X'},
{'X','X','O','X'},
{'X','O','X','X'},
}
solve(board)
fmt.Println("Updated Board:")
for _, row := range board {
fmt.Println(string(row))
}
}Rust implementation
fn dfs(board: &mut Vec<Vec<char>>, r: isize, c: isize) {
let rows = board.len() as isize;
let cols = board[0].len() as isize;
if r < 0 || c < 0 || r >= rows || c >= cols || board[r as usize][c as usize] != 'O' {
return;
}
board[r as usize][c as usize] = '#';
dfs(board, r + 1, c);
dfs(board, r - 1, c);
dfs(board, r, c + 1);
dfs(board, r, c - 1);
}
fn solve(board: &mut Vec<Vec<char>>) {
let rows = board.len();
let cols = board[0].len();
for i in 0..rows {
if board[i][0] == 'O' {
dfs(board, i as isize, 0);
}
if board[i][cols - 1] == 'O' {
dfs(board, i as isize, (cols - 1) as isize);
}
}
for j in 0..cols {
if board[0][j] == 'O' {
dfs(board, 0, j as isize);
}
if board[rows - 1][j] == 'O' {
dfs(board, (rows - 1) as isize, j as isize);
}
}
for i in 0..rows {
for j in 0..cols {
if board[i][j] == 'O' {
board[i][j] = 'X';
} else if board[i][j] == '#' {
board[i][j] = 'O';
}
}
}
}
fn main() {
let mut board = vec![
vec!['X', 'X', 'X', 'X'],
vec!['X', 'O', 'O', 'X'],
vec!['X', 'X', 'O', 'X'],
vec!['X', 'O', 'X', 'X'],
];
solve(&mut board);
println!("Updated Board:");
for row in &board {
println!("{:?}", row);
}
}Kotlin implementation
fun dfs(board: Array<CharArray>, r: Int, c: Int) {
val rows = board.size
val cols = board[0].size
if (r < 0 || c < 0 || r >= rows || c >= cols || board[r][c] != 'O') return
board[r][c] = '#'
dfs(board, r + 1, c)
dfs(board, r - 1, c)
dfs(board, r, c + 1)
dfs(board, r, c - 1)
}
fun solve(board: Array<CharArray>) {
val rows = board.size
val cols = board[0].size
for (i in 0 until rows) {
if (board[i][0] == 'O') dfs(board, i, 0)
if (board[i][cols - 1] == 'O') dfs(board, i, cols - 1)
}
for (j in 0 until cols) {
if (board[0][j] == 'O') dfs(board, 0, j)
if (board[rows - 1][j] == 'O') dfs(board, rows - 1, j)
}
for (i in 0 until rows) {
for (j in 0 until cols) {
if (board[i][j] == 'O') board[i][j] = 'X'
if (board[i][j] == '#') board[i][j] = 'O'
}
}
}
fun main() {
val board = arrayOf(
charArrayOf('X','X','X','X'),
charArrayOf('X','O','O','X'),
charArrayOf('X','X','O','X'),
charArrayOf('X','O','X','X')
)
solve(board)
println("Updated Board:")
for (row in board) {
println(row.joinToString(" "))
}
}Swift implementation
func dfs(_ board: inout [[Character]], _ r: Int, _ c: Int) {
let rows = board.count
let cols = board[0].count
if r < 0 || c < 0 || r >= rows || c >= cols || board[r][c] != "O" {
return
}
board[r][c] = "#"
dfs(&board, r + 1, c)
dfs(&board, r - 1, c)
dfs(&board, r, c + 1)
dfs(&board, r, c - 1)
}
func solve(_ board: inout [[Character]]) {
let rows = board.count
let cols = board[0].count
for i in 0..<rows {
if board[i][0] == "O" { dfs(&board, i, 0) }
if board[i][cols - 1] == "O" { dfs(&board, i, cols - 1) }
}
for j in 0..<cols {
if board[0][j] == "O" { dfs(&board, 0, j) }
if board[rows - 1][j] == "O" { dfs(&board, rows - 1, j) }
}
for i in 0..<rows {
for j in 0..<cols {
if board[i][j] == "O" {
board[i][j] = "X"
} else if board[i][j] == "#" {
board[i][j] = "O"
}
}
}
}
var board: [[Character]] = [
["X","X","X","X"],
["X","O","O","X"],
["X","X","O","X"],
["X","O","X","X"]
]
solve(&board)
print("Updated Board:")
for row in board {
print(row.map { String($0) }.joined(separator: " "))
}TypeScript implementation
function solve(board: string[][]): string[][] {
const rows = board.length;
const cols = board[0].length;
function dfs(r: number, c: number): void {
if (r < 0 || c < 0 || r >= rows || c >= cols || board[r][c] !== 'O') return;
board[r][c] = '#';
dfs(r + 1, c);
dfs(r - 1, c);
dfs(r, c + 1);
dfs(r, c - 1);
}
for (let i = 0; i < rows; i++) {
if (board[i][0] === 'O') dfs(i, 0);
if (board[i][cols - 1] === 'O') dfs(i, cols - 1);
}
for (let j = 0; j < cols; j++) {
if (board[0][j] === 'O') dfs(0, j);
if (board[rows - 1][j] === 'O') dfs(rows - 1, j);
}
for (let i = 0; i < rows; i++) {
for (let j = 0; j < cols; j++) {
if (board[i][j] === 'O') board[i][j] = 'X';
if (board[i][j] === '#') board[i][j] = 'O';
}
}
return board;
}
const board: string[][] = [
["X", "X", "X", "X"],
["X", "O", "O", "X"],
["X", "X", "O", "X"],
["X", "O", "X", "X"]
];
console.log("Updated Board:", solve(board));Time complexity
| Case | Time | Explanation |
|---|---|---|
| best case | O(m × n) | Even if there are no 'O's in the matrix, the algorithm must check every border element and traverse the matrix once. |
| average case | O(m × n) | Each cell is visited once during border traversal and once during the final transformation, resulting in linear complexity based on the number of cells. |
| worst case | O(m × n) | If the entire matrix is filled with 'O's, DFS/BFS could touch each element multiple times, but the total work remains bounded by O(m × n). |
Space complexity
O(m × n)
In the worst case, a DFS/BFS queue or recursion stack can hold all cells in the matrix when marking connected regions.