Leetcode

Subtitle / Summary This is Hot100 article #1 for the series: Subarray Sum Equals K. We reduce the naive O(n^2) approach to O(n) with prefix sum plus a frequency hash map, then map the same pattern to real engineering scenarios. Reading time: 12-15 min Tags: Hot100, prefix sum, hash map SEO keywords: Subarray Sum Equals K, prefix sum, hash map, O(n), Hot100 Meta description: O(n) counting of subarrays with sum k using prefix sum + hash map, with complexity analysis and runnable multi-language code. Target Readers Hot100 learners who want stable reusable templates Intermediate engineers who want to transfer counting patterns to real data pipelines Interview prep readers who want to master prefix sum + hash map Background / Motivation “Count subarrays whose sum equals k” is one of the most classic counting problems. It appears in log analytics, risk threshold hits, and transaction sequence statistics. The two-loop brute force method is straightforward, but slows down quickly as input grows. So we need an O(n) method that scales. ...

Subtitle / Summary The key is not comparing values, but comparing node identity (same object / same address). This ACERS guide explains the naive hash approach, the length-alignment approach, and the most practical switch-head two-pointer template, with runnable multi-language implementations under the no-modification and no-cycle constraints. Reading time: 10-14 min Tags: Hot100, linked list, two pointers SEO keywords: Intersection of Two Linked Lists, switch heads, O(1) space, LeetCode 160 Meta description: Two pointers walk A then B and B then A, guaranteeing meeting at the intersection or both reaching null within m+n steps, with O(m+n) time and O(1) space. A - Algorithm (Problem and Algorithm) Problem Restatement Given heads headA and headB of two singly linked lists, return the node where they intersect. If they do not intersect, return null. ...

Subtitle / Summary The constraint “the path can start anywhere, but must go downward” makes root-to-leaf DP insufficient. This ACERS guide explains prefix sums on trees: convert any downward path into a difference of two prefix sums, maintain a frequency hash map during one DFS, and finish in O(n). Reading time: 12–15 min Tags: binary tree, prefix sum, DFS, hash map SEO keywords: Path Sum III, tree prefix sum, prefix-sum hash, LeetCode 437 Meta description: Count downward paths whose sum equals targetSum in O(n) via prefix sum + hash map, with derivation, tradeoffs, and multi-language implementations. A — Algorithm (Problem & Algorithm) Problem Restatement Given the root root of a binary tree and an integer targetSum, return the number of downward paths whose node values sum to targetSum. The path does not need to start at the root or end at a leaf, but it must go downward (parent → child). ...

Subtitle / Summary Spiral traversal looks like “just printing in a fancy order”, but the real difficulty is getting boundaries and invariants right. This ACERS guide gives a reusable boundary-shrinking template and runnable multi-language solutions. Reading time: 12–15 min Tags: Hot100, matrix, simulation, boundary shrinking SEO keywords: Hot100, Spiral Matrix, clockwise traversal, boundary shrinking, LeetCode 54 Meta description: O(mn) spiral order traversal using boundary shrinking, with pitfalls, engineering scenarios, and runnable code. A — Algorithm Problem Restatement Given an m × n matrix matrix, return all elements in clockwise spiral order. ...

Subtitle / Summary Trapping Rain Water is the classic boundary-constraint problem. This ACERS guide explains the two-pointer method, key formulas, and runnable multi-language solutions. Reading time: 12–15 min Tags: Hot100, two pointers, array SEO keywords: Trapping Rain Water, two pointers, left right max, O(n), Hot100 Meta description: Two-pointer O(n) trapped water solution with engineering scenarios and multi-language code. A — Algorithm Problem Restatement Given an array of non-negative integers representing bar heights (each width 1), compute how much water can be trapped after raining. ...

Subtitle / Summary Maximum Subarray is the classic 1D DP / greedy template. This ACERS guide explains Kadane’s idea, engineering use cases, and runnable multi-language solutions. Reading time: 10–12 min Tags: Hot100, dynamic programming, greedy SEO keywords: Maximum Subarray, Kadane, dynamic programming, O(n), Hot100 Meta description: Kadane O(n) maximum subarray sum with engineering scenarios and multi-language code. A — Algorithm Problem Restatement Given an integer array nums, find the contiguous subarray with the largest sum (must contain at least one element) and return the sum. ...

Subtitle / Summary A classic event-spacing validation model. This ACERS guide explains the one-pass logic, engineering use cases, and runnable multi-language solutions. Reading time: 10–12 min Tags: array, two pointers, event spacing SEO keywords: LeetCode 1437, event spacing, O(n) Meta description: One-pass validation for minimum spacing between 1s, with engineering use cases and multi-language code. A — Algorithm Problem Restatement Given an integer array nums and integer k, return true if every pair of 1s is at least k apart; otherwise return false. ...

Subtitle / Summary A classic bit-manipulation template: determine if a number is a power of two in O(1). This ACERS guide covers the core insight, practical uses, and runnable multi-language implementations. Reading time: 8–12 min Tags: bit manipulation, binary, math SEO keywords: Power of Two, bit manipulation, binary, O(1), LeetCode 231 Meta description: O(1) power-of-two check using bit tricks, with engineering scenarios and multi-language code. A — Algorithm Problem Restatement Given an integer n, determine whether it is a power of two. Return true if it is; otherwise, return false. ...

Subtitle / Summary A standard fixed-window counting problem. This ACERS guide explains the sliding-window model, engineering use cases, and runnable multi-language solutions. Reading time: 10–12 min Tags: sliding window, string, fixed window SEO keywords: Maximum Number of Vowels, Sliding Window, Fixed Window Meta description: Fixed-window sliding count for maximum vowels with engineering applications. A — Algorithm Problem Restatement Given a string s and an integer k, return the maximum number of vowels in any substring of length k. ...

Title LeetCode 239: Sliding Window Maximum (Monotonic Queue ACERS Guide) Subtitle / Summary Sliding Window Maximum is the classic combo of sliding window + monotonic queue. This article follows the ACERS template with reusable engineering patterns and multi-language implementations. Estimated reading time: 12–15 minutes Tags: sliding window, monotonic queue, array SEO keywords: Sliding Window Maximum, monotonic queue, deque, O(n) Meta description: Monotonic-queue solution for Sliding Window Maximum with engineering practice and multi-language implementations. A — Algorithm (Problem & Algorithm) Problem Restatement Given an integer array nums and a window size k, a sliding window moves from left to right. Each move shifts the window by one. Return the maximum for each window. ...