Best of Algorithms — July 2025

1
Article
Collections·44w
Mastering Data Structures and Algorithms for Coding Interviews
A comprehensive guide covering essential data structures and algorithms needed for coding interview success. Key topics include arrays, hashmaps, linked lists, binary search, graph traversal algorithms, and dynamic programming. The guide emphasizes pattern recognition over random problem solving, recommending a structured approach of mastering 100-150 problems across common coding patterns like sliding window and two pointers.
128
2
2
Article
The Polymathic Engineer·45w
How to Tackle Coding Interviews
A structured 7-step framework for succeeding in coding interviews: listen carefully to understand the problem, create meaningful examples, start with brute force solutions, optimize using BUD methodology (bottlenecks, unnecessary work, duplicated work), walk through the algorithm before coding, write clean modular code with descriptive variables, and thoroughly test the solution. The approach emphasizes communication, systematic problem-solving, and demonstrating debugging skills when issues arise.
128
1
3
Video
developedbyed·44w
Leetcode is not scary, it's actually really fun
LeetCode problems are actually enjoyable brain training exercises rather than scary interview hurdles. The key is approaching them as puzzles that build problem decomposition skills applicable to real-world programming. Starting with structured roadmaps like arrays and hashing, then gradually building intuition through practice makes the experience rewarding. Three classic problems demonstrate different approaches: two-sum shows optimization from O(n²) to O(n) using hash maps, contains duplicate leverages sets for efficient lookups, and valid anagram can be solved through character counting or string sorting techniques.
96
2
4
Video
Tech With Tim·44w
How I Mastered Data Structures and Algorithms
A practical guide to mastering data structures and algorithms efficiently for coding interviews. The approach emphasizes choosing an easy language like Python, learning theory quickly without over-studying, practicing 75-100 quality problems instead of hundreds, and simulating real interview conditions with mock interviews and whiteboard practice. The key is quality over quantity, proper preparation methodology, and building confidence through thorough practice.
43
1
5
Article
xkcd·45w
xkcd: Echo Chamber
An xkcd comic exploring the concept of echo chambers, likely commenting on how technology and social media platforms create isolated information bubbles that reinforce existing beliefs and limit exposure to diverse perspectives.
26
2
6
Article
Hacker News·44w
Algorithms for Modern Processor Architectures
Modern processors have reached frequency plateaus due to physical constraints, but offer significant optimization opportunities through SIMD instructions, memory-level parallelism, and superscalar execution. The key to performance lies in reducing instruction count and leveraging architectural features like branch prediction and parallel processing units. Practical examples demonstrate how algorithmic redesign can achieve dramatic speedups, from parsing numbers at gigabyte speeds to validating UTF-16 at one character per cycle through techniques like loop unrolling, vectorization, and finite state machines.
17
1
7
Article
DigitalOcean Community·45w
How to Use a Priority Queue in Python
Priority queues in Python can be implemented using the heapq module for single-threaded applications or queue.PriorityQueue for thread-safe operations. The heapq module provides a min-heap implementation with O(log n) time complexity for push/pop operations, while queue.PriorityQueue offers built-in synchronization for multithreaded environments. Max-heaps can be simulated by negating values or using custom comparison methods. Priority queues are essential for task scheduling, pathfinding algorithms, and any scenario requiring ordered processing based on element priority.
15
8
Video
CodeHead·46w
How Big Tech Companies Really Hire People
Big tech hiring is a chaotic mix of applicant tracking systems, recruiter screening, technical interviews, and hiring committees. The process relies heavily on referrals to bypass automated filters, involves multiple rounds of coding challenges and system design questions, and often comes down to timing and luck rather than pure merit. Despite appearing objective, outcomes can vary significantly based on interviewer preferences and team needs.
15
1
9
Article
Javarevisited·42w
How a Machine Learning Engineer Scored $750K+ Offers from Snap, Google, and Apple — Study Guide & Resources
A machine learning engineer shares their comprehensive study plan and resources that helped them secure $750K+ offers from major tech companies including Snap, Google, and Apple. The guide covers five key areas: coding interview preparation using books like CLRS and platforms like LeetCode, ML fundamentals and system design with resources like 'Dive Into Deep Learning', traditional system design concepts, behavioral interview strategies using STAR methodology, and ML-specific coding challenges. The engineer emphasizes pattern-based preparation, early focus on design topics, and leveraging AI tools like ChatGPT for mock interviews and resume optimization.
14
10
Video
Two Minute Papers·45w
Roblox Solved The Physics Problem That Stumped Everyone!
Roblox and University of Utah developed Augmented Vertex Block Descent (AVBD), a physics simulation method that solves complex collision and constraint problems that stumped previous techniques. The method can simulate millions of particles at 100 FPS on consumer graphics cards and correctly handles challenging scenarios like heavy objects on light chains, chain mail collisions, and spring-connected blocks where older methods failed completely.
14
2
11
Video
CodeHead·43w
Top 10 DSAs YOU NEED TO KNOW For Your Coding Interview
A comprehensive guide covering the 10 most essential data structures and algorithms for coding interviews, including arrays, hashmaps, stacks, queues, binary search, recursion, trees, heaps, and graphs. Each concept is explained with practical examples and common interview problem patterns, designed to help developers recognize and solve algorithmic challenges efficiently during technical interviews.
13
12
Video
ThePrimeTime·45w
THIS BLEW MY MIND
XOR (exclusive or) operations have unique properties that make them useful for solving programming problems elegantly. XOR has memory-like behavior where A XOR A equals zero and A XOR 0 equals A. These properties enable clever solutions to common interview questions like finding missing numbers in arrays, swapping variables without temporary storage, and detecting duplicates. The technique works by leveraging XOR's commutative property and the fact that duplicate values cancel each other out when XORed together. Advanced applications include finding two missing numbers by partitioning based on bit differences and implementing forward error correction in network protocols.
10

See all Algorithms archives