M H tree reachesBoth (“B”, H”) would return “G tree. reach (“F”, N”) would return “M tree. re D”) would return “D tree. reachesBoth(“X”, “M”) would return nu

**1. Implement public T reachesBoth(T a, T b) You should return the data value of the node that can reach both a and b in the least number of steps (a node can reach itself in 0 steps). If a or b is not in the tree, return null. Consider the BinaryTree tree on the left with outputs on the right: tree.reachesBoth(“B”, “H”) would return “G” tree.reachesBoth(“F”, “N”) would return “M” tree.reachesBoth(“B”, “D”) would return “D” tree.reachesBoth(“X”, “M”) would return null**

**2. Implement public T findRightmostLowest() In the above tree, there are two lowest nodes: B and F. Both of them are distance 3 from the root; all other nodes are less than distance 3. F is to the right of B so tree.findRightmostLowest() should return “F”.**

**3. Implement public T findKthLargest(int k) Consider the sorted order of all the elements in the tree. The index of the smallest element is 0. The index of the largest element is tree.size() – 1. In the above tree, tree.findKthLargest(1) would return “D” and tree.findKthLargest(4) would return “H”. Return null if k is out of range.**

**4.: Implement public void balance() Use a findKthLargest-based approach to rebalance the tree using a pivot-style approach. The new root should be the tree’s median (KthLargest index of size() / 2). Recursively, the root of each branch should be the median of each branch (index within that subtree of its size / 2). This method should not need to call new and should execute in O(n log n) time to receive full credit.**

Thanks in advance! Will rate if good. Plz start with the following code that has not been implemented yet.

import java.util.Arrays;

/**

* A binary search tree for Comparable objects such as Strings, Integers, etc.

* For each node n, all nodes to the left have data which is less than n.data

* and all nodes to the right have data which is greater than n.data.

*

* @param

*/

public class BinaryTree> {

private static class Node> {

public T data;

public Node left, right;

public void add(T d) {

int comp = d.compareTo(data);

if (comp == 0)

return; // Already in tree

if (comp < 0) {

if (left == null) {

left = new Node<>();

left.data = d;

} else {

left.add(d);

}

} else {

// Greater than

if (right == null) {

right = new Node<>();

right.data = d;

} else {

right.add(d);

}

}

}

public boolean contains(T d) {

int comp = d.compareTo(data);

if (comp == 0)

return true; // Already in tree

if (comp < 0) {

if (left == null) {

return false; // Not in the tree

} else {

return left.contains(d);

}

} else {

if (right == null) {

return false; // Not in the tree

} else {

return right.contains(d);

}

}

}

public void print(int indent) {

if (right != null)

right.print(indent + 1);

char[] spaces = new char[indent * 2];

Arrays.fill(spaces, ‘ ‘);

System.out.println(new String(spaces) + data);

if (left != null)

left.print(indent + 1);

}

/**

* The number of nodes of this subtree.

* @return Number of nodes

*/

public int size() {

// We know there is a node here

int total = 1;

// This node may have left children

if (left != null)

total = total + left.size();

// This node may have right children

if (right != null)

total = total + right.size();

// The total size of the tree from this point…

return total;

}

/**

* Delete this node.

*

* @return The new root of this subtree (null if this node had no

* children, also known as a leaf)

*/

public Node deleteNode() {

if (left == null)

return right;

if (right == null)

return left;

Node successor = right;

if (successor.left == null) {

// Case 1: no left child of immediate successor

right = right.right;

} else {

// Case 2: loop until we find leftmost child

Node successorParent = null;

while (successor.left != null) {

successorParent = successor;

successor = successor.left;

}

successorParent.left = successor.right;

}

// Replace this data with successor data

data = successor.data;

return this;

}

/**

* Deletes the node containing d if it exists.

*

* @param d

* @return A valid BinaryTree that doesn’t have d in it but does have

* everything else.

*/

public Node delete(T d) {

int comp = d.compareTo(data);

if (comp == 0)

return deleteNode();

if (comp < 0) {

// If d exists, it’s to the left

if (left != null)

left = left.delete(d);

return this;

} else {

if (right != null)

right = right.delete(d);

return this;

}

}

}

private Node root;

public BinaryTree() {

root = null;

}

/**

* Adds data to the tree if it didn’t already contain it.

*

* @param data

*/

public void add(T data) {

if (root == null) {

root = new Node<>();

root.data = data;

} else {

root.add(data);

}

}

/**

* Returns true if the tree contains data, false otherwise

*

* @param data

* Does the tree contain this?

* @return true if it does

*/

public boolean contains(T data) {

if (root == null)

return false;

return root.contains(data);

}

/**

* Prints out a representation of the tree (rotate your head 90 degrees

* left)

*/

public void print() {

if (root != null)

root.print(0);

}

/**

* Gets the number of nodes of the tree in O(n) time.

*

* @return number of nodes

*/

public int size() {

if (root == null)

return 0;

return root.size();

}

/**

* Delete the node containing data from the tree, if it exists.

*

* @param data

*/

public void delete(T data) {

root = root.delete(data);

}

/**

* Returns the data value of the node that can reach both a and b in the

* least number of steps. If the tree doesn’t contain both a and b, return

* null.

*

* @param a

* @param b

* @return data value

*/

public T reachesBoth(T a, T b) {

// TODO: Implement.

return null;

}

/**

* Among all the nodes which are farthest from the root, find the one which

* is farthest to the right.

*

* @return data value of said node

*/

public T findRightmostLowest() {

// TODO: Implement.

return null;

}

/**

* Return the kth largest element according to the Comparable sorted order

* of the tree. The leftmost node has index 0 and the rightmost node has

* index size() – 1.

*

* @param k

* index

* @return element, or null if k is out of range.

*/

public T findKthLargest(int k) {

// TODO: Implement.

return null;

}

/**

* EXTRA CREDIT: Balance the tree. The new root should be the

* findKthLargest(size()/2) node. Recursively, the root of each subtree

* should also be the size/2-largest node (indexed from 0) of that subtree.

* This method should not call new and should execute in O(n log n) time for

* full credit.

*/

public void balance() {

// TODO: Implement for extra credit.

}

}

Here’s your code, i have added comments for the new functions that are added:

import java.util.Arrays;

/**

* A binary search tree for Comparable objects such as Strings, Integers, etc.

* For each node n, all nodes to the left have data which is less than n.data

* and all nodes to the right have data which is greater than n.data.

*

* @param

*/

public class BinaryTree<T extends Comparable<T>> {

private static class Node<T extends Comparable<T>> {

public T data;

public Node<T> left, right;

public void add(T d) {

int comp = d.compareTo(data);

if (comp == 0)

return; // Already in tree

if (comp < 0) {

if (left == null) {

left = new Node<>();

left.data = d;

} else {

left.add(d);

}

} else {

// Greater than

if (right == null) {

right = new Node<>();

right.data = d;

} else {

right.add(d);

}

}

}

public boolean contains(T d) {

int comp = d.compareTo(data);

if (comp == 0)

return true; // Already in tree

if (comp < 0) {

if (left == null) {

return false; // Not in the tree

} else {

return left.contains(d);

}

} else {

if (right == null) {

return false; // Not in the tree

} else {

return right.contains(d);

}

}

}

public void print(int indent) {

if (right != null)

right.print(indent + 1);

char[] spaces = new char[indent * 2];

Arrays.fill(spaces, ‘ ‘);

System.out.println(new String(spaces) + data);

if (left != null)

left.print(indent + 1);

}

/**

* The number of nodes of this subtree.

* @return Number of nodes

*/

public int size() {

// We know there is a node here

int total = 1;

// This node may have left children

if (left != null)

total = total + left.size();

// This node may have right children

if (right != null)

total = total + right.size();

// The total size of the tree from this point…

return total;

}

/**

* Delete this node.

*

* @return The new root of this subtree (null if this node had no

* children, also known as a leaf)

*/

public Node deleteNode() {

if (left == null)

return right;

if (right == null)

return left;

Node successor = right;

if (successor.left == null) {

// Case 1: no left child of immediate successor

right = right.right;

} else {

// Case 2: loop until we find leftmost child

Node successorParent = null;

while (successor.left != null) {

successorParent = successor;

successor = successor.left;

}

successorParent.left = successor.right;

}

// Replace this data with successor data

data = (T)successor.data;

return this;

}

/**

* Deletes the node containing d if it exists.

*

* @param d

* @return A valid BinaryTree that doesn’t have d in it but does have

* everything else.

*/

public Node delete(T d) {

int comp = d.compareTo(data);

if (comp == 0)

return deleteNode();

if (comp < 0) {

// If d exists, it’s to the left

if (left != null)

left = left.delete(d);

return this;

} else {

if (right != null)

right = right.delete(d);

return this;

}

}

}

private Node root;

public BinaryTree() {

root = null;

}

/**

* Adds data to the tree if it didn’t already contain it.

*

* @param data

*/

public void add(T data) {

if (root == null) {

root = new Node<>();

root.data = data;

} else {

root.add(data);

}

}

/**

* Returns true if the tree contains data, false otherwise

*

* @param data

* Does the tree contain this?

* @return true if it does

*/

public boolean contains(T data) {

if (root == null)

return false;

return root.contains(data);

}

/**

* Prints out a representation of the tree (rotate your head 90 degrees

* left)

*/

public void print() {

if (root != null)

root.print(0);

}

/**

* Gets the number of nodes of the tree in O(n) time.

*

* @return number of nodes

*/

public int size() {

if (root == null)

return 0;

return root.size();

}

/**

* Delete the node containing data from the tree, if it exists.

*

* @param data

*/

public void delete(T data) {

root = root.delete(data);

}

/*

This is a recursive helper function to compute reaches both

*/

private T reachesBothAtNode(T a, T b, Node<T> n) {

if(n==null) {

// reached at the bottom and neither a nor b were seen

return null;

}

if(a.compareTo(n.data) == 0) {

// the current node has value a

// if the node contains b anywhere then this is where it reaches both a and b

return n.contains(b) ? a : null;

}

if(b.compareTo(n.data) == 0) {

// the current node has value b

// if the node contains a anywhere then this is where it reaches both a and b

return n.contains(a) ? b : null;

}

if(a.compareTo(n.data) < 0 && b.compareTo(n.data) < 0) {

// both a and b are less than current node value

// if there’s a node that reaches both, it must be in the left subtree

return reachesBothAtNode(a, b, n.left);

}

if(a.compareTo(n.data) > 0 && b.compareTo(n.data) > 0) {

// both a and b are greater than current node value

// if there’s a node that reaches both, it must be in the right subtree

return reachesBothAtNode(a, b, n.right);

}

if(a.compareTo(n.data) < 0 && b.compareTo(n.data) > 0) {

// a is less and b is greater than current node value

// a ‘could’ be in the left and b in right subtree

// if so then our current node reaches both

return (n.left).contains(a) && (n.right).contains(b) ? n.data : null;

}

if(a.compareTo(n.data) > 0 && b.compareTo(n.data) < 0) {

return (n.left).contains(b) && (n.right).contains(a) ? n.data : null;

}

return null;

}

/**

* Returns the data value of the node that can reach both a and b in the

* least number of steps. If the tree doesn’t contain both a and b, return

* null.

*

* @param a

* @param b

* @return data value

*/

public T reachesBoth(T a, T b) {

return reachesBothAtNode(a,b,(Node<T>)root);

}

/*

A class to save right most node with its height

height will be required for comparison

*/

private static class RMLWithHeight<T> {

int height;

T data;

public RMLWithHeight(int h,T d) {

height = h;

data = d;

}

}

// recursive helper method for findRightmostLowest of the tree

private RMLWithHeight<T> findRightmostLowestAtNode(Node<T> n) {

if(n.left==null && n.right==null) {

// leaf node height is 0

return new RMLWithHeight(0,n.data);

}

if(n.left == null) {

// no node on left and hence the lowest will always be on the right

RMLWithHeight<T> rmlAtRight = findRightmostLowestAtNode(n.right);

return new RMLWithHeight(rmlAtRight.height+1,rmlAtRight.data);

}

if(n.right == null) {

// no node on right and hence the lowest will always be on the right

RMLWithHeight<T> rmlAtLeft = findRightmostLowestAtNode(n.left);

return new RMLWithHeight(rmlAtLeft.height+1,rmlAtLeft.data);

}

RMLWithHeight<T> rmlAtLeft = findRightmostLowestAtNode(n.left);

RMLWithHeight<T> rmlAtRight = findRightmostLowestAtNode(n.right);

// compare heights of the trees at left and right

// return right most node at left if has a greater height

// also update the height, its one level higher than n.left

if(rmlAtLeft.height > rmlAtRight.height) {

return new RMLWithHeight(rmlAtLeft.height+1,rmlAtLeft.data);

}

// in case right has less or equivalent height, return right most node at right

// also update the height, its one level higher than n.right

return new RMLWithHeight(rmlAtRight.height+1,rmlAtRight.data);

}

/**

* Among all the nodes which are farthest from the root, find the one which

* is farthest to the right.

*

* @return data value of said node

*/

public T findRightmostLowest() {

RMLWithHeight<T> rml = findRightmostLowestAtNode((Node<T>)root);

return rml.data;

}

public Node<T> findKthLargestAtNode(int k, Node<T> n) {

if(n==null) {

return null;

}

int i = 0; // number of nodes in left sub-tree

if(n.left != null) {

i = (n.left).size();

}

// i is the number of nodes in the tree smaller that the node n

if(i > k) {

// kth smallest element must be less that the current node and hence in the left subtree

return findKthLargestAtNode(k, n.left);

}

if(i == k) {

// kth smallest element is the current node

// since the number of elements less than the current node is k

return n;

}

if(i < k) {

// kth smallest element must be more that the current node

// and hence in the right subtree

// the index of current node is i

// and everything on right is greater that the current node

return findKthLargestAtNode(k-i-1, n.right);

}

return null;

}

/**

* Return the kth largest element according to the Comparable sorted order

* of the tree. The leftmost node has index 0 and the rightmost node has

* index size() – 1.

*

* @param k

* index

* @return element, or null if k is out of range.

*/

public T findKthLargest(int k) {

Node<T> knn = findKthLargestAtNode(k,(Node<T>)root);

if (knn == null) {

return null;

}

return knn.data;

}

public void balanceAtNode(Node<T> n, Node<T> parent, boolean isLeft) {

if(n==null) {

return;

}

int k = n.size()/2;

Node<T> mid = findKthLargestAtNode(k,n);

int i=0;

if(mid.left != null) {

i = (mid.left).size();

}

if (mid == n) {

balanceAtNode(mid.left, mid, true);

balanceAtNode(mid.right, mid, false);

} else {

Node

tmp = n;

Node prev = null;

while(true) {

if(mid.data.compareTo((T)tmp.data)<0) {

prev = tmp;

tmp = prev.left;

} else if (mid.data.compareTo((T)tmp.data)>0) {

prev = tmp;

tmp = prev.right;

} else {

break;

}

}

boolean copy_left = true;

if(i==k) {

copy_left = false;

}

if(prev.right == mid) {

if(copy_left) {

prev.right = mid.left;

mid.left = n;

} else {

prev.right = mid.right;

mid.right = n;

}

} else {

if(copy_left) {

prev.left = mid.left;

mid.left = n;

} else {

prev.left = mid.right;

mid.right = n;

}

}

balanceAtNode(mid.left, mid, true);

balanceAtNode(mid.right, mid, false);

}

if(parent == null) {

root = mid;

} else if(isLeft) {

parent.left = mid;

} else {

parent.right = mid;

}

}

/**

* EXTRA CREDIT: Balance the tree. The new root should be the

* findKthLargest(size()/2) node. Recursively, the root of each subtree

* should also be the size/2-largest node (indexed from 0) of that subtree.

* This method should not call new and should execute in O(n log n) time for

* full credit.

*/

public void balance() {

balanceAtNode((Node<T>) root, null, true);

}

}

A sample test program:

Ouput screenshot:

sample test program to test the bonus function:

Output screenshot:

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