S.No. | Problem | Approach/Logic used | Level | Link | Solution |
---|---|---|---|---|---|
1 | Build Tree Recursively | Easy | view | view | |
2 | Count Leaf Nodes | traverse the tree through any traversal technique and just check one condition if the node has no left subtree and no right subtree then increase the count | Easy | view | view |
3 | Tree Traversals | Easy | view | view | |
4 | BT Representation | Easy | view | view | |
5 | Height of Binary Tree | Easy | view | view | |
6 | Diameter/width of a BT | Medium | view | view | |
7 | Balanced Tree or Not | Easy | view | view | |
8 | Tree Identical or Not | Easy | view | view | |
9 | Sum Tree or Not | Medium | view | view | |
10 | BT Level Order Traversal | Medium | view | view | |
11 | Sum of Longest Bloodline | Medium | view | view |
S.No. | Problem | Approach/Logic used | Level | Link | Solution |
---|---|---|---|---|---|
1 | Validate BST | Easy | view | view | |
2 | Two sum in BST | Medium | view | view | |
3 | Flatten BST to Sorted Linked List | Medium | view | view | |
4 | Normal BST to Balanced BST | Medium | view | view | |
5 | Merge two BSTs | Medium | view | view | |
6 | Largest BST in a BT | Hard | view | view |
S.No. | Problem | Approach/Logic used | Level | Link | Solution |
---|---|---|---|---|---|
1 | Insertion and Deletion in Heap | view | view | ||
2 | Build Min Heap | Easy | view | view | |
3 | Heap Sort | Medium | view | view | |
4 | Merge two heaps | Easy | view | view | |
5 | Convert BST to Max Heap | bst property(inorder of bst is sorted) and postorder has been used | Medium | view | view |
6 | Kth Smallest | using priority queue as maxheap | Easy | view | view |
7 | Is BT Heap | Heap follows two properties that's heap should be a CBT(complete BT) and should follow heap order property either max/min heap order | Medium | view | view |
8 | kth largest sum subarray | two approaches, one is using nested for loop and another one is using min heap | Medium | view | view |
9 | Merge K Sorted Arrays | two approaches | Medium | view | view |
10 | Smallest Range from K sorted list | 3 approaches | Hard | view | view |
11 | Median in a Stream | two approaches, one is bruteforce and another is using min and max heaps | Hard | view | view |
S.No. | Problem | Approach/Logic used | Level | Link | Solution |
---|---|---|---|---|---|
1 | Implementation of graph using Adjacency List | view | view | ||
2 | Implementation of graph using Adjacency Matrix | view | view | ||
3 | Creating and Printing | Easy | view | view | |
4 | BFS in Graph | Medium | view | view | |
5 | DFS in Graph | Medium | view | view | |
6 | Cycle Detection in Undirected Graphs using BFS | BFS and a condition visited[neighbour]==true and neighbour!=parent[front] |
Medium | view | view |
7 | Cycle Detection in Undirected Graphs using DFS | DFS and a condition visited[neighbour]==true and neighbour!=parent |
Medium | view | view |
8 | Cycle Detection in directed Graphs using DFS | Medium | view | view | |
9 | Topological Sort | Medium | view | view | |
10 | TopoSort using Kanh's algo | Medium | view | view | |
11 | Cycle Detection in directed graph using TopoSort | Medium | view | view | |
12 | Shortest Path in Undirected graph | Medium | view | view | |
13 | Shortest Path in DAG | Medium | view | view |