Fading Coder

One Final Commit for the Last Sprint

Advanced Algorithmic Patterns: Sorting, Binary Search, and Greedy Strategies

Sorting with Custom Logic The standard library function std::sort is a highly efficient tool for ordering data, typically implementing a variation of quicksort with a time complexity of O(n log n). While it is defined in the <algorithm> header, it is commonly accessed via <bits/stdc++.h>...

Binary Search Techniques: Core Templates and Advanced Application Patterns

The foundation of efficient search operations relies on the divide-and-conquer principle applied to monotonic or structured datasets. The standard implementation maintains two pointers, typically left and right, converging toward a target state. To prevant infinite loops and ansure precise boundary...

Two Efficient Methods for the ZAB-Frogs Grid Path Problem

We consider a rectangular grid of size \(n \times m\) with a start cell \((s_x, s_y)\) and an end cell \((e_x, e_y)\). There are \(s\) "bad" cells that act as centers of circles with equal radius \(R\). A cell is blocked if its Euclidean distance to any bad cell is \(\le R\). The goal is t...

Binary Search in Java: Three Common Template Implementations and Use Cases

Time and Space Complexity of Binary Search Time Complexity — O(log N) Binary search operates by repeatedly dividing the array in half. Each iteration reduces the search space to half of its previous size. Starting with N elements, the size becomes N/2, then N/4, and so forth untill the element is fo...

Maximizing the Minimum Gap by Removing Rocks with Binary Search

A river contains a starting rock at position 0 and an ending rock at position L. Between them there are N intermediate rocks, each at a distinct coordinate Di (0 < Di < L). A cow must jump from rock to rock, never skipping ahead by less than some distance. To challenge the cows, we can remove...

Resolving Right Interval Queries with Sorted Indices and Binary Search

The task requires identifying, for each given range [start, end], another range whose starting point is greater than or equal to the current range's ending point. Among all valid candidates, the one with the smallest starting value must be selected. The original index of this matching range is retur...

Implementing Binary Search for Left and Right Boundary Detection

When calculating the midpoint in binary search, two approach are commonly used: mid = left + (right - left) / 2 - This method prevents integer overflow by first cmoputing the interval length mid = (left + right) / 2 - This simpler form may cause overflow with large values The first approach is recom...

Binary Search for Optimization Problems

Binary search is an efficient algorithm for locating a target value within a sorted sequence. Its core principle involves repeatedly dividing the search interval in half, leveraging monotonic properties to eliminate large portions of the search space without explicit enumeration. Implementation Stra...

Dynamic Programming and Algorithm Problems Collection

Dynamic Programing Coin Change Problem def coin_change(coins, amount): dp = [float('inf')] * (amount + 1) dp[0] = 0 for coin in coins: for x in range(coin, amount + 1): dp[x] = min(dp[x], dp[x - coin] + 1) return dp[amount] if dp[amount] != float('inf') else -1 Predict the Winner def predict_winner(...

Characteristics and Applications of Binary Search for Optimization Problems

Identifying Problems Suitable for Binary Search Binary search is applicable to optimization problems with these common features: Finding the minimum possible maximum value (or maximum possible minimum value) Determining the maximum or minimum value of a variable If we denote the target value as targ...