LeetCode

This section collects Hot100 greedy tutorials, focusing on which local state is enough, why it stays valid while scanning, and how that local choice proves the global answer. Recommended Reading Order LeetCode 121: Best Time to Buy and Sell Stock, derive one-transaction greedy from the historical minimum price LeetCode 55: Jump Game, use the farthest reachable range to decide reachability LeetCode 45: Jump Game II, upgrade reachability into minimum jump layers LeetCode 435: Non-overlapping Intervals, turn minimum removals into maximum kept intervals LeetCode 452: Minimum Number of Arrows, derive interval greedy from shared intersections

This section collects Hot100 Union-Find templates and problems, focusing on set representatives, path compression, merge conditions, connectivity checks, and connected component counting.

This section collects Hot100 Trie tutorials, focusing on node fields, child traversal, end markers, and loop invariants.

Subtitle / Summary The most common confusion in LeetCode 543 is deciding what the recursive function should return. It should return height, not diameter. The diameter is updated globally at each node using leftHeight + rightHeight. Once that separation is clear, the problem becomes a clean introduction to tree DP. Reading time: 10-13 min Tags: Hot100, binary tree, tree DP, DFS, postorder SEO keywords: Diameter of Binary Tree, tree DP, height return, DFS, LeetCode 543 Meta description: Learn LeetCode 543 from the postorder height-return pattern, with step-by-step derivation, engineering analogies, and runnable multi-language solutions. A — Algorithm Problem Restatement Given the root root of a binary tree, return the diameter of the tree. ...

Subtitle / Summary The real difficulty of LeetCode 236 is not memorizing an LCA template. It is defining what each recursive call should return. Once that return value becomes stable, the whole problem collapses into a short and very clean postorder recursion. Reading time: 11-14 min Tags: Hot100, binary tree, LCA, DFS, postorder SEO keywords: Lowest Common Ancestor of a Binary Tree, LCA, postorder, DFS, LeetCode 236 Meta description: Learn LeetCode 236 from the recursive return-value semantics, with step-by-step derivation, engineering mappings, and runnable multi-language implementations. A — Algorithm Problem Restatement Given a binary tree, find the lowest common ancestor (LCA) of two given nodes p and q. ...

Subtitle / Summary The hardest part of LeetCode 98 is usually not recursion itself. It is realizing that checking a node against only its parent is not enough. A valid BST is constrained by all of its ancestors, so the stable solution is to pass a valid range downward. This guide explains that idea from scratch, then connects it to the equivalent inorder-sorted view. Reading time: 11-13 min Tags: Hot100, binary tree, BST, DFS, inorder traversal SEO keywords: Validate Binary Search Tree, BST, range constraints, inorder traversal, DFS, LeetCode 98 Meta description: Learn LeetCode 98 from the core invariant low < val < high, with step-by-step derivation, engineering mappings, and runnable multi-language implementations. A — Algorithm Problem Restatement Given the root root of a binary tree, determine whether it is a valid binary search tree (BST). ...

51. N-Queens is best learned by watching the code grow one small step at a time. This tutorial keeps only the teaching path: tiny example, first DFS skeleton, first correct version, column-only optimization, then full diagonal-state optimization. Problem The n-queens puzzle asks us to place n queens on an n x n chessboard so that no two queens attack each other. Given an integer n, return all distinct solutions. Each solution is represented as a list of strings where: ...

Subtitle / Summary 131. Palindrome Partitioning is not hard because of recursion alone. The real challenge is separating two concerns clearly: where the next cut starts, and whether the current substring is a valid palindrome. Reading time: 15-18 min Tags: Hot100, backtracking, string, palindrome, DP SEO keywords: Palindrome Partitioning, backtracking, palindrome DP, string partition, LeetCode 131 Meta description: Learn LeetCode 131 by building the solution from scratch, using suffix-based DFS plus a precomputed palindrome table. A — Algorithm Problem Restatement Given a string s, partition it so that every substring in the partition is a palindrome. Return all possible palindrome partitionings of s. ...

Subtitle / Summary 216. Combination Sum III is where backtracking adds one more important constraint: not only must the sum match, but the combination length must be exactly k. That turns the problem into a clean fixed-length combination search over the bounded range 1..9. Reading time: 12-15 min Tags: backtracking, fixed length, pruning, combination search SEO keywords: Combination Sum III, fixed-length backtracking, k numbers, pruning, LeetCode 216 Meta description: Build the stable solution for LeetCode 216 from scratch by understanding exact-length backtracking, sorted pruning, and the bounded candidate set 1..9. A — Algorithm Problem Restatement Find all valid combinations of k numbers that add up to n, subject to these rules: ...

Subtitle / Summary If 39. Combination Sum teaches “reuse is allowed”, then 40. Combination Sum II teaches the next real upgrade: duplicate values exist, each number may be used at most once, and de-duplication must happen at the correct tree level. Reading time: 14-16 min Tags: backtracking, dedup, pruning, combination search SEO keywords: Combination Sum II, backtracking, same-layer dedup, pruning, LeetCode 40 Meta description: Build the stable solution for LeetCode 40 from scratch by understanding sorted pruning, use-once recursion, and the same-layer duplicate skip rule. A — Algorithm Problem Restatement Given a collection of candidate numbers candidates and a target integer target, return all unique combinations where the chosen numbers sum to target. ...

Subtitle / Summary Combination Sum is the first Hot100 backtracking problem that really mixes three ideas at once: combination-style search, a running target, and safe pruning after sorting. The point is not to jump straight to the template, but to build it step by step from the problem itself. Reading time: 14-16 min Tags: Hot100, backtracking, combination sum, pruning SEO keywords: Combination Sum, backtracking, pruning, remain, DFS Meta description: Learn LeetCode 39 by building the solution from scratch, using path, remain, repeated candidate reuse, and sorted pruning. A — Algorithm Problem Restatement Given an array of distinct integers candidates and a target integer target, return a list of all unique combinations of candidates where the chosen numbers sum to target. ...

Subtitle / Summary If Subsets teaches the skeleton of combination-style backtracking, Permutations teaches the core of state-based backtracking: at each position, choose one unused element, continue until the path length reaches n, and only then collect the answer. Reading time: 10-12 min Tags: Hot100, backtracking, permutations, DFS SEO keywords: Permutations, backtracking, used array, DFS, LeetCode 46 Meta description: Learn the stable permutation backtracking template for LeetCode 46, with state recovery, engineering analogies, and runnable multi-language solutions. A — Algorithm Problem Restatement Given an array nums of distinct integers, return all possible permutations. The answer may be returned in any order. ...

Subtitle / Summary Clone Graph is not a traversal-only problem. The real challenge is preserving graph structure while avoiding duplicate copies in the presence of cycles. The stable solution is a traversal plus a hash map from original nodes to cloned nodes. Reading time: 12-15 min Tags: graph, dfs, bfs, hash map, deep copy SEO keywords: Clone Graph, graph deep copy, DFS, BFS, LeetCode 133 Meta description: Deep-copy an undirected graph with a node-to-node map, explaining why memoization is mandatory and how DFS/BFS versions work, with runnable code in six languages. Target Readers LeetCode learners practicing graph traversal and deep-copy patterns Engineers who duplicate object graphs, workflow graphs, or topology graphs Developers who want one reusable template for “clone with cycles” Background / Motivation Many “copy” problems are actually identity-preservation problems. ...