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

Time Complexity: Number of Islands BFS and DFS

O(n * m)

Understanding Time Complexity

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

How does the search through the grid affect the total steps taken?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

void dfs(std::vector<std::vector<char>>& grid, int r, int c) {
    int nr = grid.size();
    int nc = grid[0].size();
    if (r < 0 || c < 0 || r >= nr || c >= nc || grid[r][c] == '0') return;
    grid[r][c] = '0';
    dfs(grid, r - 1, c);
    dfs(grid, r + 1, c);
    dfs(grid, r, c - 1);
    dfs(grid, r, c + 1);
}

int numIslands(std::vector<std::vector<char>>& grid) {
    int count = 0;
    for (int r = 0; r < grid.size(); r++) {
        for (int c = 0; c < grid[0].size(); c++) {
            if (grid[r][c] == '1') {
                dfs(grid, r, c);
                count++;
            }
        }
    }
    return count;
}
    

This code counts islands by visiting each cell and exploring connected land cells using DFS.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Visiting each cell once during DFS or BFS.
• How many times: Each cell is checked once in the nested loops, and each land cell is visited once during DFS.

How Execution Grows With Input

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

Input Size (n x m)	Approx. Operations
10 x 10	About 100 visits
100 x 100	About 10,000 visits
1000 x 1000	About 1,000,000 visits

Pattern observation: The operations grow roughly with the total number of cells, so doubling rows and columns quadruples work.

Final Time Complexity

Time Complexity: O(n * m)

This means the time grows proportionally to the total number of cells in the grid.

Common Mistake

[X] Wrong: "DFS runs multiple times for each island, so time is more than O(n*m)."

[OK] Correct: Each cell is visited only once because visited land cells are marked, so total work is still proportional to grid size.

Interview Connect

Understanding this helps you explain how to efficiently explore connected areas in grids, a common problem in coding interviews.

Self-Check

"What if the grid was very sparse with few land cells? How would the time complexity change if we used BFS instead of DFS?"

Practice

1. What does the "Number of Islands" problem ask you to find in a 2D grid of '1's (land) and '0's (water)?

easy

A. Count total number of '1's in the grid

B. Count how many separate groups of connected '1's exist

C. Find the largest island size

D. Find the shortest path between two islands

Solution

1. Step 1: Understand the problem definition

   The problem asks to count distinct islands, where an island is a group of connected '1's horizontally or vertically.

2. Step 2: Clarify what is being counted

   We count how many separate clusters of '1's exist, not the total number of '1's or sizes.

3. Final Answer:

   Count how many separate groups of connected '1's exist -> Option B

4. Quick Check:

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

Hint: Islands = groups of connected '1's, count groups not cells [OK]

Common Mistakes:

• Counting total '1's instead of groups
• Including diagonal connections as connected
• Confusing island size with island count

2. Which of the following C++ code snippets correctly initializes a 2D vector grid of chars with given rows and columns filled with '0'?

easy

A. std::vector grid(rows, std::vector<char>(cols, '0'));

B. std::vector<char> grid(rows, std::vector<char>(cols, '0'));

C. std::vector grid(cols, std::vector<char>(rows, '0'));

D. std::vector grid(rows, cols, '0');

Solution

1. Step 1: Understand 2D vector initialization syntax

   To create a 2D vector of chars, use vector of vectors: outer vector size = rows, inner vector size = cols.

2. Step 2: Check each option

   std::vector grid(rows, std::vector<char>(cols, '0')); correctly creates 'rows' vectors each with 'cols' chars initialized to '0'. Others have wrong types or parameters.

3. Final Answer:

   std::vector grid(rows, std::vector<char>(cols, '0')); -> Option A

4. Quick Check:

   2D vector init = vector of vectors with sizes [OK]

Hint: Use vector(rows, vector<char>(cols, '0')) [OK]

Common Mistakes:

• Swapping rows and cols sizes
• Using wrong vector types
• Trying to initialize 2D vector with three parameters

3. Given the following grid and BFS-based code snippet to count islands, what is the output?

std::vector grid = {
  {'1','1','0','0'},
  {'1','0','0','1'},
  {'0','0','1','1'},
  {'0','0','0','0'}
};
int countIslands(const std::vector& grid) {
  int count = 0;
  int rows = grid.size();
  int cols = grid[0].size();
  std::vector visited(rows, std::vector<bool>(cols, false));
  std::queue> q;
  int directions[4][2] = {{1,0},{-1,0},{0,1},{0,-1}};
  for(int i=0; i=0 && nr=0 && nc

medium

A. 3

B. 4

C. 2

D. 1

Solution

1. Step 1: Identify islands in the grid

   Islands are groups of connected '1's. Here, islands are: top-left cluster (3 cells), single '1' at (1,3), and bottom cluster (2 cells at (2,2),(2,3)). Total 3 islands.

2. Step 2: Understand BFS traversal

   The BFS marks all connected '1's visited per island, so count increments once per island found.

3. Final Answer:

   3 -> Option A

4. Quick Check:

   Count islands = 3 [OK]

Hint: Count connected groups by BFS marking visited [OK]

Common Mistakes:

• Counting diagonal connections as islands
• Missing isolated '1's as separate islands
• Not marking visited correctly causing overcount

4. The following DFS code for counting islands has a bug. What is the bug?

void dfs(int r, int c, std::vector& grid) {
  int rows = grid.size();
  int cols = grid[0].size();
  if(r < 0 || c < 0 || r >= rows || c >= cols || grid[r][c] == '0')
    return;
  grid[r][c] = '0';
  dfs(r+1, c, grid);
  dfs(r-1, c, grid);
  dfs(r, c+1, grid);
  dfs(r, c-1, grid);
}

int numIslands(std::vector& grid) {
  int count = 0;
  for(int i=0; i

medium

A. The base case does not check for visited cells

B. The DFS does not check boundaries correctly

C. The DFS does not mark visited cells, causing infinite recursion

D. The grid is modified during DFS, which is incorrect

Solution

1. Step 1: Analyze DFS grid modification

   The DFS marks visited cells by changing '1' to '0' in the original grid, modifying input.

2. Step 2: Identify why this is a bug

   Modifying input grid may be unintended side effect; better to use a separate visited array to avoid altering input data.

3. Final Answer:

   The grid is modified during DFS, which is incorrect -> Option D

4. Quick Check:

   Modifying input grid = bug [OK]

Hint: Avoid changing input grid; use visited array instead [OK]

Common Mistakes:

• Ignoring that grid is changed in-place
• Assuming no visited tracking needed
• Misreading boundary checks as incorrect

5. You want to count islands in a grid where diagonal connections also count as connected (8 directions). How should you modify the BFS or DFS approach?

hard

A. Count islands by summing all '1's without traversal

B. Only check horizontal neighbors, ignore vertical and diagonal

C. Add diagonal directions (like (1,1), (1,-1), (-1,1), (-1,-1)) to the directions array

D. Use BFS for horizontal and DFS for vertical connections separately

Solution

1. Step 1: Understand connectivity change

   Diagonal connections mean neighbors include 8 directions: up, down, left, right, and 4 diagonals.

2. Step 2: Modify directions array

   Add diagonal moves (1,1), (1,-1), (-1,1), (-1,-1) to directions used in BFS or DFS to explore all connected neighbors.

3. Final Answer:

   Add diagonal directions (like (1,1), (1,-1), (-1,1), (-1,-1)) to the directions array -> Option C

4. Quick Check:

   Include all 8 neighbors for diagonal connectivity [OK]

Hint: Add diagonal moves to directions for 8-way connectivity [OK]

Common Mistakes:

• Ignoring diagonal neighbors
• Counting only horizontal or vertical neighbors
• Trying to count without traversal