Level-Order Traversal

Visit a tree breadth-first with a queue.

Algorithm

The canonical tree is 4(2(1,3),6(5,7)), so this Rust DSA implementation can be compared directly with the rest of the DSA track.

Basic Implementation

basic.rs

use std::collections::VecDeque;
struct Node { value: i32, left: Option<Box<Node>>, right: Option<Box<Node>> }
impl Node {
    fn new(value: i32) -> Self { Self { value, left: None, right: None } }
    fn with(value: i32, left: Node, right: Node) -> Self {
        Self { value, left: Some(Box::new(left)), right: Some(Box::new(right)) }
    }
}
fn render(node: &Option<Box<Node>>) -> String {
    match node {
        None => "_".to_string(),
        Some(n) => {
            if n.left.is_none() && n.right.is_none() { n.value.to_string() }
            else { format!("{}({},{})", n.value, render(&n.left), render(&n.right)) }
        }
    }
}
fn sample_tree() -> Option<Box<Node>> {
    Some(Box::new(Node::with(4, Node::with(2, Node::new(1), Node::new(3)), Node::with(6, Node::new(5), Node::new(7)))))
}
fn list_string(values: &[i32]) -> String {
    format!("[{}]", values.iter().map(|v| v.to_string()).collect::<Vec<_>>().join(", "))
}
fn main() { let root = sample_tree(); let mut output = Vec::new(); let mut queue: VecDeque<&Node> = VecDeque::new(); queue.push_back(root.as_ref().unwrap()); while let Some(node) = queue.pop_front() { output.push(node.value); if let Some(left) = &node.left { queue.push_back(left); } if let Some(right) = &node.right { queue.push_back(right); } } println!("{}", list_string(&output)); }

Complexity

Time: O(n)
Space: O(w) queue space

Implementation notes

Render tree structure explicitly instead of printing node objects.
The replay highlights the node, traversal state, queue, path, or search cursor that changes at each step.

level order Level-order traversal uses a queue to visit shallower nodes first.