Best of AlgorithmsFebruary 2025

  1. 1
    Video
    Avatar of youtubeYouTube·1y

    I was bad at Data Structures and Algorithms. Then I did this.

    Andrew shares a detailed roadmap on how he learned data structures and algorithms from scratch. Despite not having a computer science degree, he self-taught these concepts using free online resources and various courses, and now works as a software engineer. He emphasizes the importance of Big O notation, recommends resources like YouTube tutorials and certain books, and advises on practical coding practice with platforms like CodeWars and LeetCode. He also suggests using ChatGPT for additional help and maintaining a fun and consistent learning approach.

  2. 2
    Article
    Avatar of francofernandoThe Polymathic Engineer·1y

    How (not to) fail a coding interview

    Coding interviews require specific preparation and are different from daily work. Common mistakes include not fully understanding the problem, not asking questions, not planning before coding, not thinking out loud, ignoring hints, not testing solutions, and not knowing Big O notation. Avoiding these can improve your performance. Project-based learning is recommended for skill development.

  3. 3
    Article
    Avatar of supabaseSupabase·1y

    Postgres as a Graph Database: (Ab)using pgRouting

    pgRouting is a Postgres extension primarily used for geospatial routing and shortest path calculations, often in combination with PostGIS. Beyond GIS, it offers lightweight graph functionality for task scheduling, resource allocation in distributed systems, and recommendation engines. It supports key algorithms like Dijkstra and A* for solving complex routing problems in graph-based structures.

  4. 4
    Article
    Avatar of hnHacker News·1y

    [2111.12800] Tiny Pointers

    The post introduces the concept of tiny pointers, a new data-structural object that can replace traditional log n-bit pointers with smaller o (log n)-bit tiny pointers with minimal time overhead. It provides theoretical foundations and optimal constructions for both fixed-size and variable-size tiny pointers, showing significant space-efficiency improvements in various data structure problems without sacrificing performance.