This article walks through an interview-style solution for removing duplicates from a non‑strictly increasing sorted array in place, explaining the fast‑slow pointer technique, providing Java code, and analyzing its O(n) time and O(1) space complexities.
This article introduces the sliding window algorithmic technique, explains its relation to TCP flow control, demonstrates its implementation with Java code for maximum subarray sum, longest substring without repeats, and minimum window substring problems, and provides a reusable framework for solving similar LeetCode challenges.
This article explains the sliding‑window technique for solving the classic “Longest Substring Without Repeating Characters” problem, presents step‑by‑step analysis, demonstrates three Java implementations—from a basic set‑based method to hashmap and array optimizations—and discusses their time‑complexity improvements.
This article reviews several practical algorithm tricks—including using n&(n‑1) to clear the lowest set bit, counting bits, converting numbers, applying double‑pointer methods to linked lists and sorted arrays, and leveraging XOR properties—to simplify typical interview coding problems.
