Why Number of Islands BFS and DFS in DSA Rust?

The Big Idea

What if you could count all islands on a map perfectly without missing a single one or counting twice?

The Scenario

Imagine you have a big map made of squares, where some squares are water and some are land. You want to count how many separate islands of land there are. Doing this by looking at each square and trying to remember which ones you already counted is like trying to count friends in a crowded room without any system.

The Problem

Manually checking each square and remembering which lands belong to which island is slow and confusing. You might count the same island twice or miss some parts. It's easy to get lost and make mistakes, especially when islands are close or oddly shaped.

The Solution

Using BFS (Breadth-First Search) or DFS (Depth-First Search) helps you explore each island fully before moving to the next. These methods systematically visit all connected land squares, marking them as counted, so you never double count or miss any part.

Before vs After

✗ Before

let mut count = 0;
for i in 0..rows {
    for j in 0..cols {
        if grid[i][j] == '1' {
            count += 1; // but no way to mark visited
        }
    }
}

✓ After

fn dfs(grid: &mut Vec<Vec<char>>, i: usize, j: usize) {
    if i >= grid.len() || j >= grid[0].len() || grid[i][j] == '0' {
        return;
    }
    grid[i][j] = '0';
    if i > 0 { dfs(grid, i - 1, j); }
    dfs(grid, i + 1, j);
    if j > 0 { dfs(grid, i, j - 1); }
    dfs(grid, i, j + 1);
}

let mut count = 0;
for i in 0..rows {
    for j in 0..cols {
        if grid[i][j] == '1' {
            dfs(&mut grid, i, j);
            count += 1;
        }
    }
}

What It Enables

It enables you to quickly and correctly count all islands, no matter how complex their shapes or sizes, without missing or double counting any.

Real Life Example

Think of a drone flying over a flooded area taking pictures. It needs to count how many separate dry land patches (islands) are left to plan rescue operations. BFS or DFS helps the drone's software do this accurately and fast.

Key Takeaways

Manual counting is confusing and error-prone.

BFS and DFS explore connected lands fully to avoid mistakes.

This method helps count islands quickly and correctly.

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 largest island size in the grid

B. Count how many '0's are in the grid

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

D. Calculate the perimeter of all islands combined

Solution

1. Step 1: Understand the grid content

   The grid contains '1's representing land and '0's representing water.

2. Step 2: Define the problem goal

   The problem asks to count how many separate groups of connected '1's exist, called islands.

3. Final Answer:

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

4. Quick Check:

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

Hint: Islands = groups of connected '1's, count them [OK]

Common Mistakes:

• Confusing island count with largest island size
• Counting '0's instead of '1's
• Calculating perimeter instead of count

2. Which Rust code snippet correctly initializes a 2D vector grid of chars for the Number of Islands problem?

easy

A. let grid: Vec<char> = vec!['1', '0', '0', '1'];

B. let grid: Vec = vec![vec!['1', '0'], vec!['0', '1']];

C. let grid: Vec = vec![vec![1, 0], vec![0, 1]];

D. let grid = [[1, 0], [0, 1]];

Solution

1. Step 1: Identify correct data type for grid

   The grid should be a 2D vector of chars because the problem uses '1' and '0' as characters.

2. Step 2: Check syntax for 2D vector initialization

   let grid: Vec = vec![vec!['1', '0'], vec!['0', '1']]; uses Vec with vec! macro and char literals '1' and '0', which is correct Rust syntax.

3. Final Answer:

   let grid: Vec = vec![vec!['1', '0'], vec!['0', '1']]; -> Option B

4. Quick Check:

   2D vector of chars with vec! and '1'/'0' chars [OK]

Hint: Use Vec with vec![vec!['1', '0'], ...] [OK]

Common Mistakes:

• Using integer types instead of char
• Using arrays without specifying type
• Using 1D vector instead of 2D

3. Given the following Rust code using DFS to count islands, what is the output?

fn main() {
    let mut grid = vec![
        vec!['1', '1', '0', '0'],
        vec!['1', '0', '0', '1'],
        vec!['0', '0', '1', '1'],
        vec!['0', '0', '0', '0'],
    ];
    println!("{}", num_islands(&mut grid));
}

fn num_islands(grid: &mut Vec) -> i32 {
    let mut count = 0;
    for i in 0..grid.len() {
        for j in 0..grid[0].len() {
            if grid[i][j] == '1' {
                dfs(grid, i, j);
                count += 1;
            }
        }
    }
    count
}

fn dfs(grid: &mut Vec, i: usize, j: usize) {
    if i >= grid.len() || j >= grid[0].len() || grid[i][j] == '0' {
        return;
    }
    grid[i][j] = '0';
    if i > 0 { dfs(grid, i - 1, j); }
    dfs(grid, i + 1, j);
    if j > 0 { dfs(grid, i, j - 1); }
    dfs(grid, i, j + 1);
}

medium

A. 5

B. 4

C. 2

D. 3

Solution

1. Step 1: Identify islands in the grid

   The grid has these islands: - Top-left corner: (0,0),(0,1),(1,0) - Single '1' at (1,3) - Connected '1's at (2,2),(2,3)

2. Step 2: Count islands after DFS marks visited

   DFS marks connected '1's as '0' to avoid recounting. Total islands found = 3.

3. Final Answer:

   3 -> Option D

4. Quick Check:

   Count connected groups = 3 [OK]

Hint: Count connected '1' groups, DFS marks visited [OK]

Common Mistakes:

• Counting diagonal connections as islands
• Not marking visited cells
• Off-by-one errors in loops

4. The following Rust DFS code for Number of Islands has a bug. What is the bug?

fn dfs(grid: &mut Vec, i: usize, j: usize) {
    if i > grid.len() || j > grid[0].len() || grid[i][j] == '0' {
        return;
    }
    grid[i][j] = '0';
    if i > 0 { dfs(grid, i - 1, j); }
    dfs(grid, i + 1, j);
    if j > 0 { dfs(grid, i, j - 1); }
    dfs(grid, i, j + 1);
}

medium

A. The boundary check uses '>' instead of '>=' causing out-of-bounds panic

B. The grid is not marked visited correctly

C. The DFS does not check for diagonal neighbors

D. The function does not return the island count

Solution

1. Step 1: Analyze boundary condition in DFS

   The code checks if i > grid.len() or j > grid[0].len(), but valid indices go up to len()-1, so i == len() is out-of-bounds.

2. Step 2: Correct boundary check to prevent panic

   Use i >= grid.len() and j >= grid[0].len() to avoid accessing invalid indices and crashing.

3. Final Answer:

   The boundary check uses '>' instead of '>=' causing out-of-bounds panic -> Option A

4. Quick Check:

   Use >= for boundary checks to avoid panic [OK]

Hint: Use >= for boundary checks to avoid index errors [OK]

Common Mistakes:

• Using > instead of >= in boundary checks
• Forgetting to mark visited cells
• Ignoring out-of-bounds errors

5. You want to modify the Number of Islands BFS solution to also return the size of the largest island. Which change is correct?

hard

A. Add a counter inside BFS to count connected '1's and track max size

B. Count '1's in the grid before BFS and return that count

C. Use DFS instead of BFS without any modification

D. Return the total number of '0's as the largest island size

Solution

1. Step 1: Understand BFS traversal for islands

   BFS visits all connected '1's in an island. Counting visited nodes during BFS gives island size.

2. Step 2: Track and update largest island size

   Maintain a counter inside BFS for current island size, update max size after BFS completes for each island.

3. Final Answer:

   Add a counter inside BFS to count connected '1's and track max size -> Option A

4. Quick Check:

   Count nodes during BFS to find largest island size [OK]

Hint: Count nodes during BFS, update max size [OK]

Common Mistakes:

• Counting '1's before BFS (not island size)
• Using DFS without counting size
• Returning count of '0's instead of island size