Decode the Coding Interview in Scala: Real-World Examples/

...

/

Binary Tree Right Side View

Binary Tree Right Side View

Understand and solve the interview question "Binary Tree Right Side View".

We'll cover the following...

Description

You are given a binary tree T. Imagine you are standing to the right of it; you have to return the value of the nodes you can see from top to bottom.

You have to return the rightmost nodes on their respective levels in the form of an array.

Let’s discuss an example below:

Coding exercise

class TreeNode(var value:Int=0, var left:TreeNode=null, var right:TreeNode=null) {
}
object Solution {
  def rightSideView(root: TreeNode): Array[Int] = {
    // write your code here
    Array[Int]()
  }
}
Binary tree right side view

Solution

We can use a depth-first search (DFS) to solve this problem. The intuition here is to traverse the tree level by level recursively, starting from the rightmost node for each recursive call.

Let’s review the implementation below:

import scala.collection.mutable.ListBuffer
object Main {
  class TreeNode(var value:Int=0, var left:TreeNode=null, var right:TreeNode = null){
  }
  def DFS(node: TreeNode, level: Int, rightside: ListBuffer[Int]): Unit = {
    if (level == rightside.size) rightside.addOne(node.value)
    if (node.right != null) DFS(node.right, level + 1, rightside)
    if (node.left != null) DFS(node.left, level + 1, rightside)
  }
  def rightSideView(root: TreeNode): ListBuffer[Int] = {
    val rightside = new ListBuffer[Int]
    if (root == null) return rightside
    DFS(root, 0, rightside)
    rightside
  }
  def main(args: Array[String]): Unit = {
    val root = new TreeNode(1)
    root.left = new TreeNode(2)
    root.right = new TreeNode(3)
    root.left.left = new TreeNode(4)
    root.left.right = new TreeNode(5)
    root.right.left = new TreeNode(6)
    root.right.right = new TreeNode(7)
    root.right.right.left = new TreeNode(8)
    println("" + rightSideView(root))
  }
}
Binary tree right side view

Complexity measures

Time Complexity
...