~/lc-grind

Design a data structure that efficiently maintains the median of a dynamic data stream using two heaps for optimal O(log n) insertions and O(1) median retrieval.

Master efficient techniques like heap, bucket sort, or quickselect to solve this classic problem of finding the top K frequent elements in an array—optimal solutions go beyond basic sorting!

Solve the **Word Search II** problem by finding all words from a given list that can be constructed on an m×n board using adjacent letters, employing backtracking and a Trie for optimal efficiency—perfect for mastering matrix traversal and advanced search techniques!

Learn how to implement a **Trie (Prefix Tree)**—a powerful data structure for efficient string storage and retrieval—with methods to `insert`, `search`, and check for prefixes, perfect for autocomplete and spellchecker systems.

Learn how to efficiently find the lowest common ancestor of two nodes in a binary search tree by leveraging BST properties with a clean recursive or iterative approach.

Find the kth smallest element in a Binary Search Tree (BST) efficiently using in-order traversal or iterative DFS, with a follow-up on optimizing for dynamic BSTs.

Learn how to validate a binary search tree (BST) by ensuring every node follows the BST property—left children are smaller and right children are larger—using efficient depth-first traversal.

Learn how to reconstruct a binary tree from its preorder and inorder traversal arrays using divide-and-conquer and hash tables for efficient lookups.

Check if a binary tree contains another binary tree as a subtree, matching both structure and node values, using DFS or hashing techniques.

Master binary tree serialization and deserialization by designing efficient algorithms to convert a tree into a string and reconstruct it back, tackling this Hard problem with creative DFS/BFS or custom parsing approaches.