Maximum Width of Binary Tree in DSA Rust - Time & Space Complexity

Time Complexity: Maximum Width of Binary Tree

O(n)

Understanding Time Complexity

We want to understand how the time needed to find the maximum width of a binary tree changes as the tree grows.

Specifically, how does the number of nodes affect the work done?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

use std::collections::VecDeque;

fn width_of_binary_tree(root: Option<&Box>) -> usize {
    if root.is_none() { return 0; }
    let mut max_width = 0;
    let mut queue = VecDeque::new();
    queue.push_back((root.unwrap(), 0));

    while !queue.is_empty() {
        let level_length = queue.len();
        let first_index = queue.front().unwrap().1;
        let mut last_index = 0;

        for _ in 0..level_length {
            let (node, idx) = queue.pop_front().unwrap();
            let curr_index = idx - first_index;
            if let Some(left) = &node.left {
                queue.push_back((left, 2 * curr_index + 1));
            }
            if let Some(right) = &node.right {
                queue.push_back((right, 2 * curr_index + 2));
            }
            last_index = curr_index;
        }
        max_width = max_width.max(last_index + 1);
    }
    max_width
}

struct TreeNode {
    val: i32,
    left: Option>,
    right: Option>,
}

This code finds the maximum width of a binary tree by level-order traversal using a queue.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The while loop that visits each node once.
• How many times: Each node is processed exactly once in the queue.

How Execution Grows With Input

As the number of nodes (n) increases, the code visits each node once, so the work grows directly with n.

Input Size (n)	Approx. Operations
10	About 10 visits to nodes
100	About 100 visits to nodes
1000	About 1000 visits to nodes

Pattern observation: The operations grow linearly as the tree size grows.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the maximum width grows in direct proportion to the number of nodes in the tree.

Common Mistake

[X] Wrong: "The time depends on the height of the tree only."

[OK] Correct: The code visits every node, not just the height levels, so the total nodes matter more than height alone.

Interview Connect

Understanding this helps you explain how breadth-first search works and why visiting all nodes is necessary to find maximum width.

Self-Check

"What if we used depth-first search instead of breadth-first search? How would the time complexity change?"

Practice

1. What does the "maximum width" of a binary tree represent?

easy

A. The total number of nodes in the tree

B. The height of the tree from root to the deepest leaf

C. The largest number of nodes present at any single level of the tree

D. The sum of values of all nodes at the widest level

Solution

1. Step 1: Understand the definition of width in a binary tree

   The width of a binary tree at a level is the count of nodes present at that level.

2. Step 2: Identify maximum width

   The maximum width is the largest such count among all levels.

3. Final Answer:

   The largest number of nodes present at any single level of the tree -> Option C

4. Quick Check:

   Width = max nodes at any level [OK]

Hint: Width means count of nodes at widest level [OK]

Common Mistakes:

• Confusing width with tree height
• Thinking width is sum of node values
• Mixing width with total nodes count

2. Which Rust data structure is most suitable to track nodes level by level when calculating maximum width of a binary tree?

easy

A. VecDeque (double-ended queue)

B. Vec (vector)

C. HashMap

D. BTreeSet

Solution

1. Step 1: Identify the need for level order traversal

   To find maximum width, we visit nodes level by level, which is a breadth-first search (BFS).

2. Step 2: Choose data structure for BFS

   BFS uses a queue to process nodes in FIFO order. Rust's VecDeque supports efficient push/pop from both ends.

3. Final Answer:

   VecDeque (double-ended queue) -> Option A

4. Quick Check:

   Use queue (VecDeque) for BFS traversal [OK]

Hint: Use VecDeque for efficient queue operations in BFS [OK]

Common Mistakes:

• Using Vec which is inefficient for queue operations
• Using HashMap which is unordered
• Using BTreeSet which is for sorted unique elements

3. Given the following Rust code snippet for maximum width calculation, what is the printed output?

struct TreeNode {
    val: i32,
    left: Option,
    right: Option,
}

fn max_width(root: Option) -> usize {
    use std::collections::VecDeque;
    if root.is_none() { return 0; }
    let mut queue = VecDeque::new();
    queue.push_back(root.unwrap());
    let mut max_width = 0;
    while !queue.is_empty() {
        let level_size = queue.len();
        max_width = max_width.max(level_size);
        for _ in 0..level_size {
            let node = queue.pop_front().unwrap();
            if let Some(left) = node.left {
                queue.push_back(left);
            }
            if let Some(right) = node.right {
                queue.push_back(right);
            }
        }
    }
    max_width
}

fn main() {
    let root = Some(Box::new(TreeNode {
        val: 1,
        left: Some(Box::new(TreeNode { val: 2, left: None, right: None })),
        right: Some(Box::new(TreeNode {
            val: 3,
            left: Some(Box::new(TreeNode { val: 4, left: None, right: None })),
            right: None,
        })),
    }));
    println!("{}", max_width(root));
}

medium

A. 3

B. 2

C. 4

D. 1

Solution

1. Step 1: Analyze the tree structure

   Level 1: Node 1 (1 node) Level 2: Nodes 2 and 3 (2 nodes) Level 3: Node 4 (1 node)

2. Step 2: Calculate maximum width

   Widths per level: 1, 2, 1 Maximum width is 2.

3. Final Answer:

   2 -> Option B

4. Quick Check:

   Max width = 2 nodes at level 2 [OK]

Hint: Count nodes per level, pick max count [OK]

Common Mistakes:

• Counting total nodes instead of per level
• Ignoring empty children in width calculation
• Confusing node values with count

4. The following Rust code attempts to compute the maximum width of a binary tree but has a bug. What is the bug?

fn max_width(root: Option) -> usize {
    use std::collections::VecDeque;
    if root.is_none() { return 0; }
    let mut queue = VecDeque::new();
    queue.push_back(root.unwrap());
    let mut max_width = 0;
    while !queue.is_empty() {
        let level_size = queue.len();
        max_width = max_width.max(level_size);
        for _ in 0..level_size {
            let node = queue.pop_front().unwrap();
            if node.left.is_some() {
                queue.push_back(node.left.unwrap());
            }
            if node.right.is_some() {
                queue.push_back(node.right.unwrap());
            }
        }
    }
    max_width
}

medium

A. Not handling empty tree case

B. Using VecDeque instead of Vec causes performance issues

C. Not updating max_width inside the loop

D. Calling unwrap() on Option without checking causes panic

Solution

1. Step 1: Identify unsafe unwrap calls

   Calling unwrap() on node.left or node.right without safely extracting causes panic if None.

2. Step 2: Correct approach

   Use if let Some(left) = node.left { queue.push_back(left); } to safely handle Options.

3. Final Answer:

   Calling unwrap() on Option without checking causes panic -> Option D

4. Quick Check:

   Unsafe unwrap causes runtime panic [OK]

Hint: Use if let to safely unwrap Options [OK]

Common Mistakes:

• Using unwrap() directly on Option fields
• Ignoring empty tree check (though present here)
• Confusing VecDeque with Vec performance

5. You want to find the maximum width of a binary tree where some levels have missing nodes between others (e.g., a sparse tree). Which approach correctly calculates the maximum width including gaps between nodes? A common method is to assign position indices to nodes as if the tree was a complete binary tree. Which Rust code snippet correctly updates the maximum width using position indices during level order traversal?

use std::collections::VecDeque;

fn max_width_with_positions(root: Option) -> usize {
    if root.is_none() { return 0; }
    let mut max_width = 0;
    let mut queue = VecDeque::new();
    queue.push_back((root.unwrap(), 0usize));
    while !queue.is_empty() {
        let level_length = queue.len();
        let first_index = queue.front().unwrap().1;
        let last_index;
        for i in 0..level_length {
            let (node, idx) = queue.pop_front().unwrap();
            let idx = idx - first_index; // normalize to prevent overflow
            if node.left.is_some() {
                queue.push_back((node.left.unwrap(), 2 * idx + 1));
            }
            if node.right.is_some() {
                queue.push_back((node.right.unwrap(), 2 * idx + 2));
            }
            if i == level_length - 1 {
                last_index = idx;
            }
        }
        max_width = max_width.max(last_index + 1);
    }
    max_width
}

hard

A. Normalize indices by subtracting first index at each level to avoid overflow

B. Use raw indices without normalization to get exact positions

C. Ignore indices and count nodes only for width

D. Use depth instead of indices for width calculation

Solution

1. Step 1: Understand position indexing

   Assigning indices as if complete binary tree helps measure width including gaps.

2. Step 2: Normalize indices to prevent overflow

   Subtracting first index at each level keeps indices small and prevents usize overflow.

3. Step 3: Calculate width as last_index - first_index + 1

   Using normalized indices, width = last_index + 1 at each level.

4. Final Answer:

   Normalize indices by subtracting first index at each level to avoid overflow -> Option A

5. Quick Check:

   Index normalization prevents overflow and calculates width correctly [OK]

Hint: Subtract first index each level to keep indices small [OK]

Common Mistakes:

• Not normalizing indices causing overflow
• Ignoring gaps by counting nodes only
• Using depth instead of position indices