javascript binary search tree implementation [closed]

Question

Anyone know of any good examples of a simple BTree implementation in Javascript? I have a bunch of "things" arriving randomly, and want to insert each one efficiently.

Ultimately, each new one will get inserted into the DOM based on where it ends up in the tree.

I can code this from scratch but would rather not reinvent any wheels.

thanks

Answer 1

If it matters, I found that storing this kind of data as a literal tree was less efficient than storing it as an already-sorted array and doing binary search on the array to splice/insert elements. JavaScript object creation is not free, apparently.

There's also the ol' encode-a-tree-in-an-array trick:

[5, 3, 7, 1, null, 6, 9, null, null, null, null, null, null] 

is the same as

      5
     / \
    3   7
   /   / \
  1   6   9

i.e. children(N[i]) = N[2i+1], N[2i+2] . I don't know if that really gives you any win in JavaScript.

If you try out some alternatives to the binary tree, could you post your findings here? :)

Answer 2

https://gist.github.com/alexhawkins/f993569424789f3be5db

function BinarySearchTree() {
    this.root = null;
}

BinarySearchTree.prototype.makeNode = function(value) {
    var node = {};
    node.value = value;
    node.left = null;
    node.right = null;
    return node;
};

BinarySearchTree.prototype.add = function(value) {
    var currentNode = this.makeNode(value);
    if (!this.root) {
        this.root = currentNode;
    } else {
        this.insert(currentNode);
    }
    return this;
};

BinarySearchTree.prototype.insert = function(currentNode) {
    var value = currentNode.value;
    var traverse = function(node) {
        //if value is equal to the value of the node, ignore
        //and exit function since we don't want duplicates
        if (value === node.value) {
            return;
        } else if (value > node.value) {
            if (!node.right) {
                node.right = currentNode;
                return;
            } else
                traverse(node.right);
        } else if (value < node.value) {
            if (!node.left) {
                node.left = currentNode;
                return;
            } else
                traverse(node.left);
        }
    };
    traverse(this.root);
};


BinarySearchTree.prototype.contains = function(value) {
    var node = this.root;
    var traverse = function(node) {
        if (!node) return false;
        if (value === node.value) {
            return true;
        } else if (value > node.value) {
            return traverse(node.right);
        } else if (value < node.value) {
            return traverse(node.left);
        }
    };
    return traverse(node);
};


/* BREADTH FIRST TREE TRAVERSAL */

/* Breadth First Search finds all the siblings at each level
   in order from left to right or from right to left. */

BinarySearchTree.prototype.breadthFirstLTR = function() {
    var node = this.root;
    var queue = [node];
    var result = [];
    while (node = queue.shift()) {
        result.push(node.value);
        node.left && queue.push(node.left);
        node.right && queue.push(node.right);
    }
    return result;
};


BinarySearchTree.prototype.breadthFirstRTL = function() {
    var node = this.root;
    var queue = [node];
    var result = [];
    while (node = queue.shift()) {
        result.push(node.value);
        node.right && queue.push(node.right);
        node.left && queue.push(node.left);
    }
    return result;
};

/*DEPTH FIRST TRAVERSALS*/

/*  preOrder is a type of depth-first traversal that tries 
    togo deeper in the tree before exploring siblings. It 
    returns the shallowest descendants first.

    1) Display the data part of root element (or current element)
    2) Traverse the left subtree by recursively calling the pre-order function.
    3) Traverse the right subtree by recursively calling the pre-order function. */

BinarySearchTree.prototype.preOrder = function() {
    var result = [];
    var node = this.root;
    var traverse = function(node) {
        result.push(node.value);
        node.left && traverse(node.left);
        node.right && traverse(node.right);
    };
    traverse(node);
    return result;
};

/*  inOrder traversal is a type of depth-first traversal
    that also tries to go deeper in the tree before exploring siblings.
    however, it returns the deepest descendents first

    1) Traverse the left subtree by recursively calling the pre-order function.
    2) Display the data part of root element (or current element)
    3) Traverse the right subtree by recursively calling the pre-order function. */

BinarySearchTree.prototype.inOrder = function() {
    var result = [];
    var node = this.root;
    var traverse = function(node) {
        node.left && traverse(node.left);
        result.push(node.value);
        node.right && traverse(node.right);
    };
    traverse(node);
    return result;
};

/*  postOrder traversal is a type of depth-first traversal
    that also tries to go deeper in the tree before exploring siblings.
    however, it returns the deepest descendents first

    1) Traverse the left subtree by recursively calling the pre-order function.
    2) Display the data part of root element (or current element)
    3) Traverse the right subtree by recursively calling the pre-order function. */


BinarySearchTree.prototype.postOrder = function() {
    var result = [];
    var node = this.root;
    var traverse = function(node) {
        node.left && traverse(node.left);
        node.right && traverse(node.right);
        result.push(node.value);
    };
    traverse(node);
    return result;
};

//find the left most node to find the min value of a binary tree;
BinarySearchTree.prototype.findMin = function() {
    var node = this.root;
    var traverse = function(node) {
        return !node.left ? node.value : traverse(node.left);
    };
    return traverse(node);
};

//find the right most node to find the max value of a binary tree;
BinarySearchTree.prototype.findMax = function() {
    var node = this.root;
    var traverse = function(node) {
        return !node.right ? node.value : traverse(node.right);
    };
    return traverse(node);
};


BinarySearchTree.prototype.getDepth = function() {
    var node = this.root;
    var maxDepth = 0;
    var traverse = function(node, depth) {
        if (!node) return null;
        if (node) {
            maxDepth = depth > maxDepth ? depth : maxDepth;
            traverse(node.left, depth + 1);
            traverse(node.right, depth + 1);
        }
    };
    traverse(node, 0);
    return maxDepth;
};


//Can you write me a function that returns all the averages of the nodes 
//at each level (or depth)?? with breadth-first traversal


BinarySearchTree.prototype.nodeAverages = function() {
    var node = this.root;
    var result = {};
    var depthAverages = [];

    var traverse = function(node, depth) {
        if (!node) return null;
        if (node) {
            if (!result[depth])
                result[depth] = [node.value];
            else
                result[depth].push(node.value);
        }
        //check to see if node is a leaf, depth stays the same if it is
        //otherwise increment depth for possible right and left nodes
        if (node.right || node.left) {
            traverse(node.left, depth + 1);
            traverse(node.right, depth + 1);
        }
    };
    traverse(node, 0);

    //get averages and breadthFirst
    for (var key in result) {
        var len = result[key].length;
        var depthAvg = 0;
        for (var i = 0; i < len; i++) {
            depthAvg += result[key][i];
        }
        depthAverages.push(Number((depthAvg / len).toFixed(2)));
    }
    return depthAverages;
};

//Convert a binary search tree to a linked-list in place. 
//In-order depth-first traversal.
function LinkedList() {
    this.head = null;
}

BinarySearchTree.prototype.convertToLinkedList = function() {

    var result = [];
    var node = this.root;
    if (!node) return null;

    var traverse = function(node) {
        node.left && traverse(node.left);
        result.push(node.value);
        node.right && traverse(node.right);
    };

    traverse(node);

    var makeNode = function(value) {
        var node = {};
        node.value = value;
        node.next = null;
        return node;
    };

    var list = new LinkedList();
    list.head = makeNode(result[0]);
    var current = list.head;

    for (var i = 1; i < result.length; i++) {
        var currentNode = makeNode(result[i]);
        current.next = currentNode;
        current = current.next;
    }
    return list;
};

//TESTS

var bst = new BinarySearchTree();
bst.add(40).add(25).add(78).add(10).add(32);
console.log('BS1', bst);

var bst2 = new BinarySearchTree();
bst2.add(10).add(20).add(30).add(5).add(8).add(3).add(9);
console.log('BST2', bst2);
console.log('BREADTHFIRST LTR', bst2.breadthFirstLTR());
console.log('BREADTHFIRST RTL', bst2.breadthFirstRTL());
console.log('PREORDER', bst2.preOrder());
console.log('INORDER', bst2.inOrder());
console.log('POSTORDER', bst2.postOrder());

/* 
BREADTHFIRST LTR [ 10, 5, 20, 3, 8, 30, 9 ]
BREADTHFIRST RTL [ 10, 20, 5, 30, 8, 3, 9 ]
PREORDER [ 10, 5, 3, 8, 9, 20, 30 ]
INORDER [ 3, 5, 8, 9, 10, 20, 30 ]
POSTORDER [ 3, 9, 8, 5, 30, 20, 10 ]
*/

var bst3 = new BinarySearchTree();
bst3.add('j').add('f').add('k').add('z').add('a').add('h').add('d');
console.log(bst3);
console.log('BREADTHFIRST LTR', bst3.breadthFirstLTR());
console.log('BREADTHFIRST RTL', bst3.breadthFirstRTL());
console.log('PREORDER', bst3.preOrder());
console.log('INORDER', bst3.inOrder());
console.log('POSTORDER', bst3.postOrder());

/*
BREADTHFIRST LTR [ 'j', 'f', 'k', 'a', 'h', 'z', 'd' ]
BREADTHFIRST RTL [ 'j', 'k', 'f', 'z', 'h', 'a', 'd' ]
PREORDER [ 'j', 'f', 'a', 'd', 'h', 'k', 'z' ]
INORDER [ 'a', 'd', 'f', 'h', 'j', 'k', 'z' ]
POSTORDER [ 'd', 'a', 'h', 'f', 'z', 'k', 'j' ]
 */


console.log(bst2.findMin()); // 3
console.log(bst2.findMax()); // 30
console.log(bst2.contains(15));
//bst2.add(55);
//bst2.add(65);
//bst3.add(75);
console.log(bst2);
console.log(bst2.getDepth()); // 3
console.log(bst2.add(7).add(50).add(80).add(98));
console.log(bst2.getDepth()); // 5
console.log(bst2.nodeAverages()); //[ 10, 12.5, 13.67, 22, 80, 98 ]

console.log(bst2.convertToLinkedList());
//[ 3, 5, 7, 8, 9, 10, 20, 30, 50, 80, 98 ]
//{ head: { value: 3, next: { value: 5, next: [Object] } } }