Basic binary Tree in JavaScript

Question

I wrote a basic binary tree in JS. Can anyone give me some feedback about my code?

I just want to know if this is the right approach, and how I can improve the tree. I am new to JavaScript and data structures.

function bst() { this.root = null; } bst.prototype.insert = function( obj ){ if ( this.root == null ){ this.root = new node(obj); } else if (this.root.value > obj){ if (this.root.left != null ){ this.root.left.insert( obj ); } else { this.root.left = new node(obj); } } else if (this.root.value < obj){ if (this.root.right != null ){ this.root.right.insert( obj ); } else { this.root.right = new node(obj); } } } function node( obj ){ this.left = null; this.right = null; this.value = obj; } node.prototype.insert = function( obj ){ if (this.value > obj){ if (this.left != null){ this.left.insert( obj ) } else{ this.left = new node(obj); } } else if (this.value < obj){ if (this.right != null){ this.right.insert( obj ) } else{ this.right = new node(obj); } } //elase duplicated key value else{ console.log("duplicated bst key") } } var bst = new bst(); bst.insert(25); bst.insert(75); bst.insert(12); bst.insert(37); bst.insert(87); bst.insert(63); console.log(bst.root.value); console.log(bst.root.left.value); console.log(bst.root.right.value); console.log(bst.root.right.left.value); console.log(bst.root.right.right.value); console.log(bst.root.right.left.right.value); 

Answer 1

I can see two obvious points:

• Constructor names are usually capitalized, to indicate that they should be invoked with new
• You've got some code duplication between bst::insert and node::insert. This even leads to the bug that you don't recognise/handle duplicate values in the root node.

So, I'd suggest:

function Bst() { this.root = null; } Bst.prototype.insert = function(obj) { if (this.root == null) { this.root = new Node(obj); } else { this.root.insert(obj); } }; 

I am new to data structures.

Binary trees are a wide field :-) First, I'm missing some other basic operations like searching, traversing, and deleting. If you have mastered these, you can go on with optimizing your tree, e.g. making it a balanced one.