Binary tree depth-first traversal

Binary tree depth-first traversal

Yesterday I brushed the three traversal problems of binary trees on leetcode. Summarize the respective non- recursive (iterative) algorithms.

• traversal of binary tree
  • Breadth- first traversal
  • depth- first traversal
    • Preorder traversal => root - left - right
    • Inorder traversal => left - root - right
    • Post -order traversal => left-right-root

preorder traversal

Application: Printing a structured document

The idea is as follows

code

var preorderTraversal = function(root) {
    const stack = []
    const res = []
    if (root) {stack.push(root)}
    while (stack.length) {
        const n = stack.pop()
        res.push(n.val)
        if(n.right) stack.push(n.right)
        if(n.left) stack.push(n.left)
    }
    return res
};
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Inorder traversal

Application: Queue operations on logarithms

The idea is as follows

code

var inorderTraversal = function(root) {
    const stack = []
    const res = []
    let p = root
    while (stack.length || p) {
        while (p) {
            stack.push(p)
            p = p.left
        }
        const n = stack.pop()
        res.push(n.val)
        p = n.right
    }
    return res
};
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post-order traversal

Application: Calculate the space occupied by all files in a directory and its subdirectories

The idea is as follows

code

var postorderTraversal = function(root) {
    const res = []
    const stack = []
    const outputStack = []
    if (root) stack.push(root)
    while (stack.length) {
        const n = stack.pop() 
        outputStack.push(n)
        n.left && stack.push(n.left)
        n.right && stack.push(n.right)
    }
    while (outputStack.length) {
        const n = outputStack.pop()
        res.push(n.val)
    }
    return res
};
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