Sliding Window Algorithm Paterns Core Implementation Template const slidingWindowSolution = (inputString) => { // Initialize tracking variables let [primaryVar, secondaryVar] = [initialValue1, initialValue2]; // Set window boundaries let windowStart = 0; const results = []; for (let windowEnd = 0...
Given an integer array prices where prices[i] represents the stock price on day i, determine the maximum profit achievable. You may engage in multiple transactions (buy one and/or sell one share of the stock each day) but can hold at most one share at any time. Buying and selling on the same day is...
Problem Analysis Given a set of bombs positioned on a number line with coordinates and explosion radii, we need to compute the total effect of chain reactions. Each bomb can detonate others within its range, and the propagation continues through connected bombs. Initial Graph Construction We first m...
Reflection enables runtime examination and dynamic invocation of class members. This technique can be applied to invoke methods defined by an interface through a concrete implementation class. Core Implementation Steps The process involves several distinct stages. Step Action 1 Define the interface....
Optimizing Prefix Sum Calculations When determining the height configuration of vertical light beams (forming a non-increasing sequence), the state of horizontal beams can be uniquely determined. By incrementally adding horizontal light beams, the dynamic programming recurrence takes the form of a p...
1. House Robber III (Binary Tree) Given a binary tree representing houses where each node has a value. Adjacent houses (parent and child) cannot both be robbed on the same night. Determine the maximum amount that can be robbed without triggering an alarm. State Definition: For each node, we track tw...
Problem Analysis and Solution Approach Handling Large Input Values The problem presents a challenging constraint where values can reach up to 264, exceeding typical integer limits. Since the solution depends only on the count of distinct digits in each number rather than the actual values, we can pr...
Problem Analysis This problem requires splitting and merging intervals with maximum profit. The solution naturally fits the interval dynamic programming paradigm. DP Formulation For any interval [l, r], we choose a split point j (where l ≤ j < r) and split it into two subintervals: [l, j] and [j+...
Knapsack Problems Knapsack problems represent one of the foundational dynamic programming concepts. Typically, either weight or value is represented as a dimension in the state space, with the smaller dimension usually chosen for optimization. When both weights and values are large, standard approac...
The edit distance problem requires transforming one string into another using the minimum number of specific operations. The allowed modifications include deleting a character, inserting a new character, or substituting an existing character. The goal is to compute the lowest cost sequence of operat...