Check if value exists in level-order sorted complete binary tree

Given a level-order sorted complete binary tree, the task is to check whether a key exists in it or not. A complete binary tree has every level except possibly the last, completely filled, with all nodes as far left as possible.


          /     \
         10      15
       /   \    /  \
      17   20  30  35
     / \   /     
    40 41 50      
Input: Node = 3
Output: No

Input: Node = 7
Output: Yes

Input: Node = 30
Output: Yes

Approach A simple O(n) solution would be to fully traverse the tree and check for the key value. However, we can leverage the information that the tree is sorted and do better in terms of time complexity.

  • Find out the level where the key may exist. Start at the root node, keep going left until a value which is greater than the key value is encountered. The level before this would contain the key, if at all the key existed in the tree. Let us assume this is level l.
  • Now, perform binary search on the nodes of l. Unlike the conventional binary search, the nodes of this level cannot be accessed directly. However, the path from the root to every node in this level can be encoded using the binary logic. For example, consider the 3rd level in the sample tree. It can contain up to 23 = 8 nodes. These nodes can be reached from the root node by going left, left, left; or by going left, left, right; and so on. If the left is denoted by 0 and the right by 1 then the possible ways to reach nodes in this level can be encoded as arr = [000, 001, 010, 011, 100, 101, 110, 111].
  • However, this array doesn’t need to be created, binary search can be applied by recursively selecting the middle index and simply generating the l-bit gray code of this index (Refer to this article).
  • In case of incomplete paths, simply check for the left part of the array. For instance, the encoded path 011 does not correspond to any value in the sample tree. Since the tree is complete, it ensures that there will be no more elements to the right.
  • If the key is found return true, else return false.

Below is the implementation of the above approach:





// C++ implementation of the approach
import java.util.*;
/* Class containing left and right 
child of current node and key value*/
class Node {
    int data;
    Node left, right;
    public Node(int item)
        data = item;
        left = right = null;
class GFG {
    /* Function to locate which level to check
    for the existence of key. */
    public static int findLevel(Node root, int data)
        // If the key is less than the root,
        // it will certainly not exist in the tree
        // because tree is level-order sorted
        if (data <
            return -1;
        // If the key is equal to the root then
        // simply return 0 (zero'th level)
        if (data ==
            return 0;
        int cur_level = 0;
        while (true) {
            root = root.left;
            // If the key is found in any leftmost element
            // then simply return true
            // No need for any extra searching
            if ( == data)
                return -2;
            // If key lies between the root data and
            // the left child's data OR if key is greater
            // than root data and there is no level
            // underneath it, return the current level
            if ( < data
                && (root.left == null
                    || > data)) {
        return cur_level;
    /* Function to traverse a binary
    encoded path and return the value
    encountered after traversal. */
    public static int traversePath(Node root,
                                   ArrayList<Integer> path)
        for (int i = 0; i < path.size(); i++) {
            int direction = path.get(i);
            // Go left
            if (direction == 0) {
                // Incomplete path
                if (root.left == null)
                    return -1;
                root = root.left;
            // Go right
            else {
                // Incomplete path
                if (root.right == null)
                    return -1;
                root = root.right;
        // Return the data at the node
    /* Function to generate gray code of 
    corresponding binary number of integer i */
    static ArrayList<Integer> generateGray(int n, int x)
        // Create new arraylist to store
        // the gray code
        ArrayList<Integer> gray = new ArrayList<Integer>();
        int i = 0;
        while (x > 0) {
            gray.add(x % 2);
            x = x / 2;
        // Reverse the encoding till here
        // Leftmost digits are filled with 0
        for (int j = 0; j < n - i; j++)
            gray.add(0, 0);
        return gray;
    /* Function to search the key in a 
    particular level of the tree. */
    public static boolean binarySearch(Node root,
                                       int start,
                                       int end,
                                       int data,
                                       int level)
        if (end >= start) {
            // Find the middle index
            int mid = (start + end) / 2;
            // Encode path from root to this index
            // in the form of 0s and 1s where
            // 0 means LEFT and 1 means RIGHT
            ArrayList<Integer> encoding = generateGray(level, mid);
            // Traverse the path in the tree
            // and check if the key is found
            int element_found = traversePath(root, encoding);
            // If path is incomplete
            if (element_found == -1)
                // Check the left part of the level
                return binarySearch(root, start, mid - 1, data, level);
            if (element_found == data)
                return true;
            // Check the right part of the level
            if (element_found < data)
                return binarySearch(root, mid + 1, end, data, level);
            // Check the left part of the level
                return binarySearch(root, start, mid - 1, data, level);
        // Key not found in that level
        return false;
    // Function that returns true if the
    // key is found in the tree
    public static boolean findKey(Node root, int data)
        // Find the level where the key may lie
        int level = findLevel(root, data);
        // If level is -1 then return false
        if (level == -1)
            return false;
        // If level is -2 i.e. key was found in any
        // leftmost element then simply return true
        if (level == -2)
            return true;
        // Apply binary search on the elements
        // of that level
        return binarySearch(root, 0, (int)Math.pow(2, level) - 1, data, level);
    // Driver code
    public static void main(String[] args)
        /* Consider the following level-order sorted tree
                       /    \ 
                      8      10 
                    /  \    /  \
                  13    23 25   30
                 / \   /
                32 40 50 
        Node root = new Node(5);
        root.left = new Node(8);
        root.right = new Node(10);
        root.left.left = new Node(13);
        root.left.right = new Node(23);
        root.right.left = new Node(25);
        root.right.right = new Node(30);
        root.left.left.left = new Node(32);
        root.left.left.right = new Node(40);
        root.left.right.left = new Node(50);
        // Keys to be searched
        int arr[] = { 5, 8, 9 };
        int n = arr.length;
        for (int i = 0; i < n; i++) {
            if (findKey(root, arr[i]))




Time Complexity: The level can be found in O(logn) time. The time to traverse any path to perform binary search is O(logn). Further, in the worst case, the level may have at most n/2 nodes.

Therefore, the time complexity of performing search becomes O(logn)*O(log(n/2)) = O(logn)^2.

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