Array

Subtitle / Summary First Missing Positive is a classic in-place indexing problem. Place each valid value x into slot x-1, then scan for the first mismatch. This ACERS guide explains the derivation, invariant, pitfalls, and production-style transfer. Reading time: 12-15 min Tags: Hot100, array, in-place hashing SEO keywords: First Missing Positive, in-place hashing, index mapping, O(n), Hot100, LeetCode 41 Meta description: O(n)/O(1) solution for First Missing Positive using in-place index placement, with complexity analysis, engineering scenarios, and runnable multi-language code. Target Readers Hot100 learners building stable array templates Intermediate developers who want to master in-place indexing techniques Engineers who need linear-time, constant-space array normalization Background / Motivation “Find the smallest missing positive” is fundamentally a placement problem. ...

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. Target Readers Hot100 learners who want a reliable “matrix simulation” template Intermediate engineers who often get boundary cases wrong Anyone working with grids (visualization, raster data, path generation) Background / Motivation Matrix problems are notorious for being “easy to code, hard to get 100% correct”. One extra loop or one missed boundary check can break single-row/single-column cases or cause duplicated output. ...

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. Target Readers Hot100 learners building core templates Engineers handling capacity/volume constraints Anyone who wants a clean O(n) solution Background / Motivation Trapped water is a proxy for “capacity under boundary constraints.” It appears in cache headroom estimation, buffer overflow analysis, and terrain capacity modeling. The naive O(n^2) method is too slow; the two-pointer approach reduces it to O(n). ...

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. Target Readers LeetCode learners building stable templates Engineers working on monitoring / risk control / behavior analytics Developers who need spacing or rate-limit validations Background / Motivation Many systems require events to be spaced apart: login failures, alarms, sensitive actions, API calls, etc. This problem maps directly to event spacing validation. A one-pass, O(1)-memory solution is ideal for real-time systems. ...

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. Target Readers People practicing LeetCode / Hot100 Mid-level developers who want a reusable “sliding window + monotonic queue” template Engineers working on real-time monitoring, log analytics, or risk control Background / Motivation Rolling-window maximum appears everywhere: latency monitoring, price spikes, temperature alerts, real-time smoothing, and many more. The brute-force approach recomputes max per window in O(nk), which is unacceptable for large n. The monotonic queue reduces it to O(n), making it the most practical engineering choice. ...

Subtitle / Abstract A basic counting problem: use frequency + combinations to drop O(n^2) to O(n). Includes engineering use cases and portable implementations. Reading time: 8-10 minutes Tags: hash-table, counting, array SEO keywords: Good Pairs, hash map, frequency Meta description: Hash counting solution for Good Pairs with complexity and code. Target readers Beginners learning hash tables and counting Engineers who want to map interview patterns to real stats tasks Interview prep for basic counting models Background / Motivation Counting equal pairs is a classic problem. A double loop is O(n^2). With frequency counting, you can solve it in linear time and scale to large data. ...