Number of Islands BFS and DFS in DSA C - Time & Space Complexity

Time Complexity: Number of Islands BFS and DFS

O(rows * cols)

Understanding Time Complexity

We want to understand how the time needed to find islands grows as the grid size increases.

How does the number of cells affect the work done by BFS or DFS?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

void dfs(char** grid, int r, int c, int rows, int cols) {
    if (r < 0 || c < 0 || r >= rows || c >= cols || grid[r][c] != '1')
        return;
    grid[r][c] = '0';
    dfs(grid, r + 1, c, rows, cols);
    dfs(grid, r - 1, c, rows, cols);
    dfs(grid, r, c + 1, rows, cols);
    dfs(grid, r, c - 1, rows, cols);
}

int numIslands(char** grid, int rows, int cols) {
    int count = 0;
    for (int i = 0; i < rows; i++) {
        for (int j = 0; j < cols; j++) {
            if (grid[i][j] == '1') {
                dfs(grid, i, j, rows, cols);
                count++;
            }
        }
    }
    return count;
}
    

This code counts islands by running DFS on each land cell and marking connected land as visited.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: DFS visits each cell connected to land once.
• How many times: Each cell is visited at most once during DFS or the main loops.

How Execution Grows With Input

As the grid size grows, the number of cells to check grows too.

Input Size (n = rows * cols)	Approx. Operations
10	About 10 visits
100	About 100 visits
1000	About 1000 visits

Pattern observation: The work grows roughly in direct proportion to the number of cells.

Final Time Complexity

Time Complexity: O(rows * cols)

This means the time needed grows linearly with the total number of cells in the grid.

Common Mistake

[X] Wrong: "DFS runs for each land cell separately, so time is O((rows*cols)^2)"

[OK] Correct: Each cell is visited only once because visited cells are marked, so DFS does not repeat work.

Interview Connect

Understanding how DFS or BFS explores grids efficiently is a key skill for many problems involving connected components.

Self-Check

"What if the grid was very sparse with few land cells? How would that affect the time complexity?"

Practice

1. What does the "Number of Islands" problem ask you to find in a grid of '1's and '0's?

easy

A. Find the longest path of '1's in the grid

B. Count how many groups of connected '1's (islands) are in the grid

C. Calculate the total number of '0's in the grid

D. Replace all '1's with '0's in the grid

Solution

1. Step 1: Understand the problem definition

   The problem asks to find how many separate groups of connected '1's exist in the grid. Each group is called an island.

2. Step 2: Identify what is counted

   We count each cluster of adjacent '1's (connected horizontally or vertically) as one island.

3. Final Answer:

   Count how many groups of connected '1's (islands) are in the grid -> Option B

4. Quick Check:

   Number of islands = count of connected '1' groups [OK]

Hint: Islands = groups of connected '1's in grid [OK]

Common Mistakes:

• Counting individual '1's instead of groups
• Including diagonal connections as connected
• Counting '0's instead of '1's

2. Which of the following is the correct way to start a DFS function to explore neighbors in a grid for the Number of Islands problem in C?

easy

A. int dfs(int row, int col, char* grid)

B. int dfs(char grid[][], int row, int col)

C. void dfs(int row, int col, int grid[][])

D. void dfs(int row, int col, char** grid, int rows, int cols)

Solution

1. Step 1: Check parameter types for grid and indices

   The grid is a 2D array of characters, passed as char** grid. Row and col are integers. Rows and cols are needed to check boundaries.

2. Step 2: Verify function signature matches common DFS pattern

   void dfs(int row, int col, char** grid, int rows, int cols) correctly uses void return type (no return needed), takes row, col, grid pointer, and grid size parameters.

3. Final Answer:

   void dfs(int row, int col, char** grid, int rows, int cols) -> Option D

4. Quick Check:

   Correct DFS signature includes grid pointer and size [OK]

Hint: DFS needs grid pointer, indices, and grid size [OK]

Common Mistakes:

• Using incorrect grid parameter type
• Missing grid size parameters
• Wrong return type for DFS

3. Given the grid:

char* grid[] = {"11000", "11000", "00100", "00011"};
int rows = 4, cols = 5;

What is the number of islands found by a correct BFS or DFS solution?

medium

A. 3

B. 2

C. 1

D. 4

Solution

1. Step 1: Visualize the grid and connected '1's

   Grid rows:
   Row 0: 1 1 0 0 0
   Row 1: 1 1 0 0 0
   Row 2: 0 0 1 0 0
   Row 3: 0 0 0 1 1
   Islands are groups of connected '1's horizontally or vertically.

2. Step 2: Count islands by grouping connected '1's

   Island 1: Top-left block (positions (0,0),(0,1),(1,0),(1,1))
   Island 2: Middle single '1' at (2,2)
   Island 3: Bottom-right block (positions (3,3),(3,4))
   Total islands = 3.

3. Final Answer:

   3 -> Option A

4. Quick Check:

   Count connected '1' groups = 3 [OK]

Hint: Count connected '1' clusters visually [OK]

Common Mistakes:

• Counting diagonal '1's as connected
• Missing isolated single '1's
• Misreading grid rows or columns

4. In the following DFS code snippet for Number of Islands, what is the bug?

void dfs(int r, int c, char** grid, int rows, int cols) {
  if (r < 0 || c < 0 || r >= rows || c >= cols || grid[r][c] == '0')
    return;
  grid[r][c] = '0';
  dfs(r+1, c, grid, rows, cols);
  dfs(r-1, c, grid, rows, cols);
  dfs(r, c+1, grid, rows, cols);
  dfs(r, c-1, grid, rows, cols);
}

medium

A. It does not check for visited cells, causing infinite recursion

B. It modifies the grid, which is not allowed

C. It correctly marks visited cells by setting '1' to '0', no bug

D. It misses diagonal neighbors in DFS

Solution

1. Step 1: Analyze how visited cells are handled

   The code sets grid[r][c] = '0' to mark visited cells, preventing revisiting.

2. Step 2: Check if this approach is valid and complete

   Marking visited by changing '1' to '0' is a common and valid method. The code checks boundaries and stops recursion correctly.

3. Final Answer:

   It correctly marks visited cells by setting '1' to '0', no bug -> Option C

4. Quick Check:

   Mark visited by changing '1' to '0' is correct [OK]

Hint: Mark visited by changing '1' to '0' is valid [OK]

Common Mistakes:

• Thinking grid modification is always wrong
• Expecting separate visited array
• Confusing diagonal neighbors as required

5. You have a grid with 1000 rows and 1000 columns filled mostly with '0's and a few scattered '1's forming small islands. Which approach is best to efficiently count islands and why?

hard

A. Use BFS with a queue to avoid deep recursion and handle large grid efficiently

B. Use DFS with recursion because it is simpler and faster for large grids

C. Use DFS but do not mark visited cells to save memory

D. Count '1's directly without traversal to save time

Solution

1. Step 1: Consider grid size and recursion limits

   A 1000x1000 grid is large. Recursive DFS may cause stack overflow due to deep recursion.

2. Step 2: Evaluate BFS advantages for large grids

   BFS uses an explicit queue and avoids deep recursion, making it safer and efficient for large grids.

3. Step 3: Check other options for correctness

   DFS without marking visited causes infinite loops. Counting '1's directly misses island grouping.

4. Final Answer:

   Use BFS with a queue to avoid deep recursion and handle large grid efficiently -> Option A

5. Quick Check:

   Large grid + avoid recursion overflow = BFS [OK]

Hint: Use BFS to avoid recursion limits on large grids [OK]

Common Mistakes:

• Using recursive DFS causing stack overflow
• Not marking visited cells causing infinite loops
• Counting '1's without grouping