How to insert element in binary tree by recursion? - binary-tree

void Btree<T>::InsertNode2(T data, BtreeNode* root)
{
if (root==NULL)
{
root = new BtreeNode (data);
return ;
}
if (data <= root->data)
InsertNode2(data, root->leftchild);
else
InsertNode2(data, root->rightchild);
}
Why isn't it right? The root can't be assigned correctly. After calling the function it's still NULL.

It almost correct. Just, as said by #DragonMoon, all you need to do is to pass root by reference
void Btree<T>::InsertNode2(T data, BtreeNode &* root)
{
if (root==NULL)
{
root = new BtreeNode (data);
return ;
}
if (data <= root->data)
InsertNode2(data, root->leftchild);
else
InsertNode2(data, root->rightchild);
}

Related

Binary tree pruning

I am new to programming so please bear with me. I was solving this question https://leetcode.com/problems/binary-tree-pruning/description/ and wrote down this solution:
TreeNode* pruneTree(TreeNode* root) {
if(root==nullptr)
return root;
pruneTree(root->left);
pruneTree(root->right);
if(root->val==0 && root->left==nullptr && root->right==nullptr) {
free(root);
return NULL;
}
return root;
}
but this returned me the same tree as original and the correct answer is as follows:
TreeNode* pruneTree(TreeNode* root) {
if(root==nullptr)
return root;
root->left=pruneTree(root->left);
root->right=pruneTree(root->right);
if(root->val==0 && root->left==nullptr && root->right==nullptr) {
free(root);
return NULL;
}
return root;
}
Can someone explain me the difference between two codes.
You don't modify nodes while process the tree.
root->left=pruneTree(root->left);
root->right=pruneTree(root->right);
VS your code
pruneTree(root->left);
pruneTree(root->right);

The left hand side and an assignemnt must be a variable

This is my code so far, but idk why Im getting this error at the temp.getLeft() = null; part.
public Node removeLeaf(){
return removeLeaf(this.root);
}
public Node removeLeaf(Node node){
Node temp;
if(node.getLeft()==null && node.getRight()==null){
temp = node.parent;
}
if(temp == null){
return null;
}
if(temp.getLeft().equals(node)&& temp.getLeft()!=null){
temp.getLeft() = null;
}
}

Sentinel node in Binary Search Trees

I was wondering if in a way to avoid having to deal with the root as a special case in a Binary Search Tree I could use some sort of sentinel root node?
public void insert(int value) {
if (root == null) {
root = new Node(value);
++size;
} else {
Node node = root;
while (true) {
if (value < node.value) {
if (node.left == null) {
node.left = new Node(value);
++size;
return;
} else {
node = node.left;
}
} else if (value > node.value) {
if (node.right == null) {
node.right = new Node(value);
++size;
return;
} else {
node = node.right;
}
} else return;
}
}
}
For instance, in the insert() operation I have to treat the root node in a special way. In the delete() operation the same will happen, in fact, it will be way worse.
I've thought a bit regarding the issue but I couldn't come with any good solution. Is it because it is simply not possible or am I missing something?
The null node itself is the sentinel, but instead of using null, you can use an instance of a Node with a special flag (or a special subclass), which is effectively the null node. A Nil node makes sense, as that is actually a valid tree: empty!
And by using recursion you can get rid of the extra checks and new Node littered all over (which is what I presume is really bothering you).
Something like this:
class Node {
private Value v;
private boolean is_nil;
private Node left;
private Node right;
public void insert(Value v) {
if (this.is_nil) {
this.left = new Node(); // Nil node
this.right = new Node(); // Nil node
this.v = v;
this.is_nil = false;
return;
}
if (v > this.v) {
this.right.insert(v);
} else {
this.left.insert(v);
}
}
}
class Tree {
private Node root;
public Tree() {
root = new Node(); // Nil Node.
}
public void insert(Value v) {
root.insert(v);
}
}
If you don't want to use recursion, your while(true) is kind of a code smell.
Say we keep it as null, we can perhaps refactor it as.
public void insert(Value v) {
prev = null;
current = this.root;
boolean left_child = false;
while (current != null) {
prev = current;
if (v > current.v) {
current = current.right;
left_child = false;
} else {
current = current.left;
left_child = true;
}
}
current = new Node(v);
if (prev == null) {
this.root = current;
return;
}
if (left_child) {
prev.left = current;
} else {
prev.right = current;
}
}
The root will always be a special case. The root is the entry point to the binary search tree.
Inserting a sentinel root node means that you will have a root node that is built at the same time as the tree. Furthermore, the sentinel as you mean it will just decrease the balance of the tree (the BST will always be at the right/left of its root node).
The only way that pops in my mind to not manage the root node as a special case during insert/delete is to add empty leaf nodes. In this way you never have an empty tree, but instead a tree with an empty node.
During insert() you just replace the empty leaf node with a non-empty node and two new empty leafs (left and right).
During delete(), as a last step (if such operation is implemented as in here) you just empty the node (it becomes an empty leaf) and trim its existing leafs.
Keep in mind that if you implement it this way you will have more space occupied by empty leaf nodes than by nodes with meaningful data. So, this implementation has sense only if space is not an issue.
The code would look something like this:
public class BST {
private Node root;
public BST(){
root = new Node();
}
public void insert(int elem){
root.insert(elem);
}
public void delete(int elem){
root.delete(elem);
}
}
public class Node{
private static final int EMPTY_VALUE = /* your empty value */;
private int element;
private Node parent;
private Node left;
private Node right;
public Node(){
this(EMPTY_VALUE, null, null, null);
}
public Node(int elem, Node p, Node l, Node r){
element = elem;
parent = p;
left = l;
right = r;
}
public void insert(int elem){
Node thisNode = this;
// this cycle goes on until an empty node is found
while(thisNode.element != EMPTY_VALUE){
// follow the correct path for the insertion here
}
// insert new element here
// thisNode is an empty node at this point
thisNode.element = elem;
thisNode.left = new Node();
thisNode.right = new Node();
thisNode.left.parent = thisNode;
thisNode.right.parent = thisNode;
}
public void delete(int elem){
// manage delete here
}
}

BST to Double-LinkedList Algorithm complexity?

I am looking at the code to do this in CC150. One of its method is as follows, it does this by retrieving the tail of the left sub-tree.
public static BiNode convert(BiNode root) {
if (root == null) {
return null;
}
BiNode part1 = convert(root.node1);
BiNode part2 = convert(root.node2);
if (part1 != null) {
concat(getTail(part1), root);
}
if (part2 != null) {
concat(root, part2);
}
return part1 == null ? root : part1;
}
public static BiNode getTail(BiNode node) {
if (node == null) {
return null;
}
while (node.node2 != null) {
node = node.node2;
}
return node;
}
public static void concat(BiNode x, BiNode y) {
x.node2 = y;
y.node1 = x;
}
public class BiNode {
public BiNode node1;
public BiNode node2;
public int data;
public BiNode(int d) {
data = d;
}
}
What I don't understand is the Time Complexity the author gives in the book O(n^2). What I came up with is T(N) = 2*T(N/2) + O(N/2), O(N/2) is consumed by the getting tail reference because it needs to traverse a list length of O(N/2). So by Master Theorem, it should be O(NlogN). Did I do anything wrong? Thank you!
public static BiNode convert(BiNode root) {//worst case BST everything
if (root == null) { // on left branch (node1)
return null;
}
BiNode part1 = convert(root.node1);//Called n times
BiNode part2 = convert(root.node2);//Single call at beginning
if (part1 != null) {
concat(getTail(part1), root);// O(n) every recursive call
} // for worst case so 1 to n
// SEE BELOW
if (part2 != null) {
concat(root, part2);
}
return part1 == null ? root : part1;
}
public static BiNode getTail(BiNode node) {//O(n)
if (node == null) {
return null;
}
while (node.node2 != null) {
node = node.node2;
}
return node;
}
public static void concat(BiNode x, BiNode y) {//O(1)
x.node2 = y;
y.node1 = x;
}
SAMPLE TREE:
4
/
3
/
2
/
1
As you can see, in the worst case scenario (Big-Oh is not average case), the BST would be structured using only the node1 branch(es). Thus, the recursion would have a have to run getTail() with '1 + 2 + ... + N' problem sizes to complete the conversion.
Which is O(n^2)

Gwt CellTable Sorting page by page only

GWT CellTable column sorting page by page only, for each page i have to click the column header
for sorting.
How to sort whole data on single header click.
This is my code,
dataProvider = new ListDataProvider<List<NamePair>>();
dataProvider.addDataDisplay(dgrid);
List<List<NamePair>> list = dataProvider.getList();
for (List<NamePair> contact : test) {
dataProvider.setList(test);
list.add(contact);
}
ListHandler<List<NamePair>> columnSortHandler = new ListHandler<List<NamePair>>(dataProvider.getList());
System.out.println("Column count->"+dgrid.getColumnCount());
for(int j=0 ; j<dgrid.getColumnCount();j++){
final int val = j;
columnSortHandler.setComparator(dgrid.getColumn(val), new Comparator<List<NamePair>>() {
public int compare(List<NamePair> o1, List<NamePair> o2) {
if (o1 == o2) {
return 0;
}
// Compare the column.
if (o1 != null) {
int index = val;
return (o2 != null) ? o1.get(index-2).compareTo(o2.get(index-2)) : 1;
}
return -1;
}
});
}
dgrid.addColumnSortHandler(columnSortHandler);
I suggest you override ListHandler , override and call super.onColumnSort(ColumnSortEvent) to debug the onColumnSort(ColumnSortEvent) method, you'll understand what is happening very fast.
The source code of the method is pretty direct
public void onColumnSort(ColumnSortEvent event) {
// Get the sorted column.
Column<?, ?> column = event.getColumn();
if (column == null) {
return;
}
// Get the comparator.
final Comparator<T> comparator = comparators.get(column);
if (comparator == null) {
return;
}
// Sort using the comparator.
if (event.isSortAscending()) {
Collections.sort(list, comparator);
} else {
Collections.sort(list, new Comparator<T>() {
public int compare(T o1, T o2) {
return -comparator.compare(o1, o2);
}
});
}
}

Resources