public static bool haspathSum(BinaryNodeInt node, int sum)
{
if (node == null)
{
return(sum == 0);
}
else
{
bool ans = false;
/* otherwise check both subtrees */
int subsum = sum - node.Value;
if (subsum == 0 && node.Left == null && node.Right == null)
{
return(true);
}
if (node.Left != null)
{
ans = ans || haspathSum(node.Left, subsum);
}
if (node.Right != null)
{
ans = ans || haspathSum(node.Right, subsum);
}
return(ans);
}
}
/// <summary>
/// 1) Create an empty stack S.
/// 2) Initialize current node as root
/// 3) Push the current node to S and set current = current->left until current is NULL
/// 4) If current is NULL and stack is not empty then
/// a) Pop the top item from stack.
/// b) Print the popped item, set current = popped_item->right
/// c) Go to step 3.
/// 5) If current is NULL and stack is empty then we are done.
/// https://www.geeksforgeeks.org/inorder-tree-traversal-without-recursion/
/// </summary>
/// <param name="root"></param>
private static void IterativeInOrderUsingStack(BinaryNodeInt root)
{
if (root == null)
{
return;
}
Stack <BinaryNodeInt> stack = new Stack <BinaryNodeInt>();
while (root != null)
{
stack.Push(root);
root = root.Left;
}
while (stack.Count > 0)
{
root = stack.Pop();
Console.Write(root.Value + " ");
if (root.Right != null)
{
root = root.Right;
while (root != null)
{
stack.Push(root);
root = root.Left;
}
}
}
}
/// <summary>
/// In fact, we could optimize this scenario by doing a breadth-first traversal (also known as
/// level-order traversal). When we encounter the first leaf node, we immediately stop the
/// traversal.
/// We also keep track of the current depth and increment it when we reach the end of level.
///
/// We know that we have reached the end of level when the current node is the right-most node.
///
/// Compared to the recursion approach, the breadth-first traversal works well for highly
/// unbalanced tree because it does not need to traverse all nodes. The worst case is when the
/// tree is a full binary tree with a total of n nodes. In this case, we have to traverse all nodes.
///
/// The worst case space complexity is O(n), due to the extra space needed to store current
/// level nodes in the queue.
/// </summary>
/// <param name="root"></param>
/// <returns></returns>
private static int MinDepthBreadthFirst(BinaryNodeInt root)
{
if (root == null)
{
return(0);
}
Queue <BinaryNodeInt> q = new Queue <BinaryNodeInt>();
q.Enqueue(root);
BinaryNodeInt rightMost = root;
int depth = 1;
while (q.Count > 0)
{
BinaryNodeInt node = q.Dequeue();
if (node.Left == null && node.Right == null)
{
break;
}
if (node.Left != null)
{
q.Enqueue(node.Right);
}
if (node.Right != null)
{
q.Enqueue(node.Right);
}
if (node == rightMost)
{
depth++;
rightMost = (node.Right != null) ? node.Right : node.Left;
}
}
return(depth);
}
/// <summary>
/// Given a binary tree, find its maximum depth.
/// The maximum depth is the number of nodes along the longest path from the root node
/// down to the farthest leaf node.
///
// We could solve this easily using recursion, because each of the left child and right child
// of a node is a sub-tree itself.We first compute the max height of left sub-tree, and then
// compute the max height of right sub-tree.The maximum depth of the current node is the
// greater of the two maximums plus one. For the base case, we look at a tree that is empty,
// which we return 0.
// Assume that n is the total number of nodes in the tree. The runtime complexity is O(n)
// because it traverse each node exactly once. As the maximum depth of a binary tree is
// O(log n), the extra space cost is O(log n) due to the extra stack space used by the
// recursion.
/// </summary>
/// <param name="root"></param>
/// <returns></returns>
private static int MaxDepth(BinaryNodeInt root)
{
if (root == null)
{
return(0);
}
return(Math.Max(MaxDepth(root.Left), MaxDepth(root.Right)) + 1);
}
private static bool valid(BinaryNodeInt p, int low, int high)
{
if (p == null)
{
return(true);
}
return((low == 0 || p.Value > low) && (high == 0 || p.Value < high) &&
valid(p.Left, low, p.Value) &&
valid(p.Right, p.Value, high));
}
/* function to print level order traversal of tree*/
private static void PrintLevelOrder(BinaryNodeInt root)
{
int h = Height(root);
int i;
for (i = 1; i <= h; i++)
{
PrintGivenLevel(root, i);
}
}
private static int SumOfAllNodes(BinaryNodeInt root)
{
if (root == null)
{
return(0);
}
else
{
return(root.Value + SumOfAllNodes(root.Left) + SumOfAllNodes(root.Right));
}
}
/* Function to print REVERSE level order traversal a tree*/
/// <summary>
/// https://www.geeksforgeeks.org/reverse-level-order-traversal/
/// </summary>
/// <param name="root"></param>
private static void PrintReverseLevelOrder(BinaryNodeInt root)
{
int h = Height(root);
int i;
for (i = h; i >= 1; i--)
//THE ONLY LINE DIFFERENT FROM NORMAL LEVEL ORDER
{
PrintGivenLevel(root, i);
}
}
private static void IterativePostOrderUsingStack(BinaryNodeInt root)
{
Stack <BinaryNodeInt> stack = new Stack <BinaryNodeInt>();
// Check for empty tree
if (root == null)
{
return;
}
stack.Push(root);
BinaryNodeInt prev = null;
while (stack.Count > 0)
{
BinaryNodeInt current = stack.Peek();
if (prev == null || prev.Left == current || prev.Right == current)
{
if (current.Left != null)
{
stack.Push(current.Left);
}
else if (current.Right != null)
{
stack.Push(current.Right);
}
else
{
stack.Pop();
Console.Write(current.Value + " ");
}
}
else if (current.Left == prev)
{
if (current.Right != null)
{
stack.Push(current.Right);
}
else
{
stack.Pop();
Console.Write(current.Value + " ");
}
}
else if (current.Right == prev)
{
stack.Pop();
Console.Write(current.Value + " ");
}
prev = current;
}
}
/* Constructed binary tree is
* 10
* / \
* 8 2
* / \ /
* 3 5 2
*/
public static void Test()
{
BinaryNodeInt root = new BinaryNodeInt(10);
root.Left = new BinaryNodeInt(8);
root.Right = new BinaryNodeInt(2);
root.Left.Left = new BinaryNodeInt(3);
root.Left.Right = new BinaryNodeInt(5);
root.Right.Left = new BinaryNodeInt(2);
Console.Write("Sum of all nodes is: " + SumOfAllNodesInBinaryTree.SumOfAllNodes(root));
}
public static void Test()
{
BinaryNodeInt root = new BinaryNodeInt(1);
root.Left = new BinaryNodeInt(2);
root.Right = new BinaryNodeInt(3);
root.Left.Left = new BinaryNodeInt(4);
root.Left.Right = new BinaryNodeInt(5);
// 1 2 4 5 3
Console.Write("Preorder traversal of binary tree is \n");
RecursivePostOrder(root);
Console.Write("\n");
IterativePostOrderUsingStack(root);
}
/// <summary>
/// Algorithm Preorder(tree)
/// 1. Visit the root.
/// 2. Traverse the left subtree, i.e., call Preorder(left-subtree)
/// 3. Traverse the right subtree, i.e., call Preorder(right-subtree)
/// https://www.geeksforgeeks.org/tree-traversals-inorder-preorder-and-postorder/
/// </summary>
private static void RecursivePreOrder(BinaryNodeInt node)
{
if (node == null)
{
return;
}
/* first print data of node */
Console.Write(node.Value + " ");
/* then recur on left sutree */
RecursivePreOrder(node.Left);
/* now recur on right subtree */
RecursivePreOrder(node.Right);
}
/* Given a binary tree, print its nodes in inorder*/
/// <summary>
/// Algorithm Inorder(tree)
/// 1. Traverse the left subtree, i.e., call Inorder(left-subtree)
/// 2. Visit the root.
/// 3. Traverse the right subtree, i.e., call Inorder(right-subtree)
/// https://www.geeksforgeeks.org/tree-traversals-inorder-preorder-and-postorder/
/// </summary>
/// <param name="node"></param>
private static void RecursiveInOrder(BinaryNodeInt node)
{
if (node == null)
{
return;
}
/* first recur on left child */
RecursiveInOrder(node.Left);
/* then print the data of node */
Console.Write(node.Value + " ");
/* now recur on right child */
RecursiveInOrder(node.Right);
}
/// <summary>
/// Algorithm Postorder(tree)
/// 1. Traverse the left subtree, i.e., call Postorder(left-subtree)
/// 2. Traverse the right subtree, i.e., call Postorder(right-subtree)
/// 3. Visit the root.
/// https://www.geeksforgeeks.org/tree-traversals-inorder-preorder-and-postorder/
/// </summary>
/// <param name="node"></param>
private static void RecursivePostOrder(BinaryNodeInt node)
{
if (node == null)
{
return;
}
// first recur on left subtree
RecursivePostOrder(node.Left);
// then recur on right subtree
RecursivePostOrder(node.Right);
// now deal with the node
Console.Write(node.Value + " ");
}
/* Print nodes at the given level */
private static void PrintGivenLevel(BinaryNodeInt root, int level)
{
if (root == null)
{
return;
}
if (level == 1)
{
Console.Write(root.Value + " ");
}
else if (level > 1)
{
PrintGivenLevel(root.Left, level - 1);
PrintGivenLevel(root.Right, level - 1);
}
}
private static void ReverseTree(BinaryNodeInt root)
{
if (root == null)
{
return;
}
// swap root.left with root.right
BinaryNodeInt temp = root.Right;
root.Right = root.Left;
root.Left = temp;
ReverseTree(root.Left);
ReverseTree(root.Right);
}
public static void Test()
{
BinaryNodeInt root = new BinaryNodeInt(1);
root.Left = new BinaryNodeInt(2);
root.Right = new BinaryNodeInt(3);
root.Left.Left = new BinaryNodeInt(4);
root.Left.Right = new BinaryNodeInt(5);
Console.Write("level traversal of binary tree is \n");
PrintLevelOrder(root);
Console.Write("\n");
PrintLevelOrderUsingQueue(root);
Console.Write("\n");
PrintReverseLevelOrder(root);
Console.Write("\n");
PrintReverseLevelOrderUsingQueueStack(root);
}
/// <summary>
/// 1. Initialize current as root
/// 2. While current is not NULL
/// If current does not have left child
/// a) Print current’s data
/// b) Go to the right, i.e., current = current->right
/// Else
/// a) Make current as right child of the rightmost node in current's left subtree
/// b) Go to this left child, i.e., current = current->left
/// https://www.geeksforgeeks.org/inorder-tree-traversal-without-recursion-and-without-stack/
/// </summary>
/// <param name="root"></param>
private static void IterativeInOrderUsingNonStack(BinaryNodeInt root)
{
if (root == null)
{
return;
}
BinaryNodeInt current, pre;
current = root;
while (current != null)
{
if (current.Left == null)
{
Console.Write(current.Value + " ");
current = current.Right;
}
else
{
/* Find the inorder predecessor of current */
pre = current.Left;
while (pre.Right != null && pre.Right != current)
{
pre = pre.Right;
}
/* Make current as right child of its inorder predecessor */
if (pre.Right == null)
{
pre.Right = current;
current = current.Left;
}
/* Revert the changes made in if part to restore the
* original tree i.e.,fix the right child of predecssor*/
else
{
pre.Right = null;
Console.Write(current.Value + " ");
current = current.Right;
} /* End of if condition pre->right == NULL */
} /* End of if condition current->left == NULL*/
}
}
/// <summary>
/// We could avoid the recalculation by passing the depth bottom-up.We use a sentinel value –1
/// to represent that the tree is unbalanced so we could avoid unnecessary calculations.
///
/// In each step, we look at the left subtree’s depth(L), and ask: “Is the left subtree
/// unbalanced?” If it is indeed unbalanced, we return –1 right away.Otherwise, L represents
/// the left subtree’s depth. We then repeat the same process for the right subtree’s depth (R).
///
/// We calculate the absolute difference between L and R.If the subtrees’ depth difference is
/// less than one, we could return the height of the current node, otherwise return –1 meaning
/// the current tree is unbalanced.
/// </summary>
/// <param name="root"></param>
/// <returns></returns>
private static int MaxDepth(BinaryNodeInt root)
{
if (root == null)
{
return(0);
}
int L = MaxDepth(root.Left);
if (L == -1)
{
return(-1);
}
int R = MaxDepth(root.Right);
if (R == -1)
{
return(-1);
}
return((Math.Abs(L - R) <= 1) ? (Math.Max(L, R) + 1) : -1);
}
/// <summary>
/// The idea is to use a stack to get the reverse level order.
/// If we do normal level order traversal and instead of printing a node,
/// push the node to a stack and then print contents of stack, we get “5 4 3 2 1” for above example tree,
/// but output should be “4 5 2 3 1”.
/// So to get the correct sequence (left to right at every level),
/// we process children of a node in reverse order,
/// we first push the right subtree to stack, then left subtree.
/// https://www.geeksforgeeks.org/reverse-level-order-traversal/
/// </summary>
/// <param name="root"></param>
private static void PrintReverseLevelOrderUsingQueueStack(BinaryNodeInt node)
{
Stack <BinaryNodeInt> S = new Stack <BinaryNodeInt>();
Queue <BinaryNodeInt> Q = new Queue <BinaryNodeInt>();
Q.Enqueue(node);
// Do something like normal level order traversal order.Following
// are the differences with normal level order traversal
// 1) Instead of printing a node, we push the node to stack
// 2) Right subtree is visited before left subtree
while (Q.Count > 0)
{
/* Dequeue node and make it root */
node = Q.Peek();
Q.Dequeue();
S.Push(node);
/* Enqueue right child */
if (node.Right != null)
{
// NOTE: RIGHT CHILD IS ENQUEUED BEFORE LEFT
Q.Enqueue(node.Right);
}
/* Enqueue left child */
if (node.Left != null)
{
Q.Enqueue(node.Left);
}
}
// Now pop all items from stack one by one and print them
while (S.Count > 0)
{
node = S.Peek();
Console.Write(node.Value + " ");
S.Pop();
}
}
/// <summary>
/// Algorithm:
/// There are basically two functions in this method.One is to print all nodes at a given level(printGivenLevel),
/// and other is to print level order traversal of the tree(printLevelorder).
/// printLevelorder makes use of printGivenLevel to print nodes at all levels one by one starting from root.
/// /*Function to print level order traversal of tree*/
/// printLevelorder(tree)
/// for d = 1 to height(tree)
/// printGivenLevel(tree, d);
/// /*Function to print all nodes at a given level*/
/// printGivenLevel(tree, level)
/// if tree is NULL then return;
/// if level is 1, then
/// print(tree->data);
/// else if level greater than 1, then
/// printGivenLevel(tree->left, level-1);
/// printGivenLevel(tree->right, level-1);
/// </summary>
/// <param name="root"></param>
/// <returns></returns>
/* Compute the "height" of a tree -- the number of
* nodes along the longest path from the root node
* down to the farthest leaf node.*/
private static int Height(BinaryNodeInt root)
{
if (root == null)
{
return(0);
}
else
{
/* compute height of each subtree */
int lheight = Height(root.Left);
int rheight = Height(root.Right);
/* use the larger one */
if (lheight > rheight)
{
return(lheight + 1);
}
else
{
return(rheight + 1);
}
}
}
// Time Complexity: O(n^2) in worst case. For a skewed tree,
// printGivenLevel() takes O(n) time where n is the number of nodes in the skewed tree.
// So time complexity of printLevelOrder() is O(n) + O(n-1) + O(n-2) + .. + O(1) which is O(n^2).
// Method 2: Use Queue
///Algorithm:
///For each node, first the node is visited and then it’s child nodes are put in a FIFO queue.
///
/// printLevelorder(tree)
/// 1) Create an empty queue q
/// 2) temp_node = root /*start from root*/
/// 3) Loop while temp_node is not NULL
/// a) print temp_node->data.
/// b) Enqueue temp_node’s children(first left then right children) to
/// c) Dequeue a node from q and assign it’s value to temp_node
/// <summary>
/// Given a binary tree. Print its nodes in level order using array for implementing queue
/// </summary>
private static void PrintLevelOrderUsingQueue(BinaryNodeInt root)
{
Queue <BinaryNodeInt> queue = new Queue <BinaryNodeInt>();
queue.Enqueue(root);
while (queue.Count > 0)
{
BinaryNodeInt tempNode = queue.Dequeue();
Console.Write(tempNode.Value + " ");
/*Enqueue left child */
if (tempNode.Left != null)
{
queue.Enqueue(tempNode.Left);
}
/*Enqueue right child */
if (tempNode.Right != null)
{
queue.Enqueue(tempNode.Right);
}
}
}
/// <summary>
/// PreOrder: root - left - right
/// To convert an inherently recursive procedures to iterative,
/// we need an explicit stack. Following is a simple stack based iterative process to print Preorder traversal.
/// 1) Create an empty stack nodeStack and push root node to stack.
/// 2) Do following while nodeStack is not empty.
/// ….a) Pop an item from stack and print it.
/// ….b) Push right child of popped item to stack
/// ….c) Push left child of popped item to stack
///
/// Right child is pushed before left child to make sure that left subtree is processed first.
/// https://www.geeksforgeeks.org/iterative-preorder-traversal/
/// </summary>
/// <param name="root"></param>
private static void IterativePreOrderUsingStack(BinaryNodeInt root)
{
// Base Case
if (root == null)
{
return;
}
// Create an empty stack and push root to it
Stack <BinaryNodeInt> nodeStack = new Stack <BinaryNodeInt>();
nodeStack.Push(root);
/* Pop all items one by one. Do following for every popped item
* a) print it
* b) push its right child
* c) push its left child
* Note that right child is pushed first so that left is processed first */
while (nodeStack.Count > 0)
{
// Pop the top item from stack and print it
BinaryNodeInt node = nodeStack.Peek();
Console.Write(node.Value + " ");
nodeStack.Pop();
// Push right and left children of the popped node to stack
if (node.Right != null)
{
nodeStack.Push(node.Right);
}
if (node.Left != null)
{
nodeStack.Push(node.Left);
}
}
}
/// <summary>
/// 10
/// / \
/// 5 15
/// / \
/// 6 20
/// We can avoid examining all nodes of both subtrees in
/// each pass by passing down the low and high limits from the parent to its children.
/// Refer back to the binary tree (1) above.As we traverse down the tree from node(10) to
/// right node(15), we know for sure that the right node’s value fall between 10 and +∞.
/// Then, as we traverse further down from node(15) to left node(6), we know for sure that
/// the left node’s value fall between 10 and 15. And since(6) does not satisfy the above
/// requirement, we can quickly determine it is not a valid BST.
/// </summary>
/// <param name="root"></param>
/// <returns></returns>
private static bool isValidBST(BinaryNodeInt root)
{
return(valid(root, 0, 0));
}
public BinaryNodeInt(int value)
{
this.Value = value;
this.Left = this.Right = null;
}
private static bool isBalanced(BinaryNodeInt root)
{
return(MaxDepth(root) != -1);
}
