Best of Data Structures — October 2024

  1. 1
    Article
    Avatar of communityCommunity Picks·2y

    1 Year of Consistent LeetCoding

    After attempting the Google Foobar challenge and going through several interview rounds with Google, the author didn't get the job but found inspiration to master data structures and algorithms. They committed to solving LeetCode problems daily, resulting in a 365+ day streak. Key learnings included efficient array manipulation, string handling, understanding hash tables, sorting algorithms, and greedy algorithms. Regular practice and tracking progress were vital in improving their skills.

  2. 2
    Video
    Avatar of youtubeYouTube·2y

    8 Data Structures Every Programmer Should Know

    Understanding fundamental data structures is crucial for optimizing code performance and problem-solving. This post covers eight essential data structures every programmer should know: arrays, linked lists, stacks, queues, hash tables, trees, heaps, and graphs. Each structure is explained with its definition, use cases, time complexities, and unique characteristics. It also emphasizes the importance of knowing which data structure to use in different programming scenarios.

  3. 3
    Article
    Avatar of c_communityC/C++ Community·2y

    C++ Mastery Roadmap: From Foundations to Advanced Applications

    A comprehensive roadmap to learning C++, covering foundational concepts, intermediate features, data structures and algorithms, advanced topics like low-level programming and GUI development with SDL, and best practices including code quality, testing, and deployment.

  4. 4
    Video
    Avatar of vscodeVisual Studio Code·2y

    Visualize data structures and algorithms

    Visualize data structures directly in VS Code using the Debug Visualizer extension. This tool allows you to run the Debug Visualizer New View command, evaluate expressions, and choose visualization methods. You can interact with visuals and observe changes in real-time, making it especially useful for learning data structures or understanding algorithms during debugging sessions.

  5. 5
    Article
    Avatar of communityCommunity Picks·2y

    TheAlgorithms/PHP: All Algorithms implemented in PHP

    The Algorithms - PHP is a library offering a set of algorithms and data structures implemented in PHP, designed to simplify their usage in development projects. Contributions are encouraged, and community support is available via Discord and Gitter.

  6. 6
    Article
    Avatar of communityCommunity Picks·2y

    The Complete [2024] Guide to Data Structures and Algorithms

    Understanding Data Structures and Algorithms (DSA) is crucial for developers and students aiming to excel in software engineering and technical interviews. This guide covers fundamental and advanced DSA concepts, offering practical examples, a structured learning path, and resources for mastering these skills. Core topics include arrays, linked lists, stacks, queues, trees, graphs, and hash tables, along with essential sorting and searching algorithms. Real-world applications and interview preparation tips are also provided, making it a comprehensive resource for mastering DSA.

  7. 7
    Video
    Avatar of teluskoTelusko·2y

    Data Structures and Algorithms (DSA) in Java 2024

    Data structures are essential for efficiently organizing and storing data to improve application performance and memory usage. They allow programmers to process data quickly and optimally, important in industries like e-commerce and banking. Understanding when to use different data structures (arrays, sets, linked lists, trees, graphs) is crucial, as is knowing how to implement efficient algorithms. Companies emphasize data structures and algorithms (DSA) as they help in reducing costs and improving user experience. Linear search and binary search are discussed to illustrate different algorithm efficiencies.

  8. 8
    Article
    Avatar of quastorQuastor Daily·2y

    How Cloudflare Optimized their Reverse Proxy with Tries

    Cloudflare optimized their reverse proxy performance by using a data structure called a trie. This change cut latency by 75% for a path handling 35 million requests per second. Their process included extensive benchmarking with the Rust criterion crate, inverting their header removal function, and creating a custom optimized trie implementation. This effort's result was a reduction in average header removal time from 3.65 to 0.93 microseconds.

See all Data Structures archives