Number of Islands BFS and DFS in DSA C - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal of the Number of Islands problem?

To count how many separate groups of connected '1's (land) exist in a 2D grid of '1's and '0's (land and water).

intermediate

How does Depth-First Search (DFS) help solve the Number of Islands problem?

DFS explores all connected land cells from a starting point by going deep into neighbors recursively, marking visited cells to avoid counting the same island multiple times.

intermediate

How does Breadth-First Search (BFS) differ from DFS in this problem?

BFS explores neighbors level by level using a queue, visiting all adjacent land cells before moving deeper, but both BFS and DFS mark visited cells to count islands correctly.

beginner

What data structure is commonly used to keep track of cells to visit in BFS for Number of Islands?

A queue is used to store cells to visit next in BFS, ensuring neighbors are processed in the order they are discovered.

beginner

Why do we mark cells as visited in Number of Islands algorithms?

Marking cells as visited prevents counting the same land cell multiple times and avoids infinite loops during traversal.

In the Number of Islands problem, what does a '1' represent in the grid?

A Visited cell

B Water

C Land

D Boundary

'1' represents land cells where islands can form.

Which traversal method uses a stack or recursion to explore deep into neighbors?

A Depth-First Search (DFS)

B Breadth-First Search (BFS)

C Binary Search

D Linear Search

DFS uses recursion or a stack to explore neighbors deeply.

What data structure does BFS use to keep track of nodes to visit next?

A Tree

B Stack

C Set

D Queue

BFS uses a queue to process neighbors in order.

Why do we mark cells as visited during traversal?

A To avoid revisiting and infinite loops

B To sort the grid

C To change their value to water

D To count them multiple times

Marking visited cells prevents revisiting and infinite loops.

Which of these is NOT a valid neighbor direction in Number of Islands problem?

A Up

B Diagonal

C Down

D Left

Only up, down, left, and right neighbors are considered, not diagonal.

Explain how DFS can be used to count the number of islands in a grid.

Think about exploring deep into connected land cells.

Describe the steps BFS follows to find all cells of an island in the grid.

Focus on level-by-level exploration using a queue.

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