A common-sense guide to data structures and algorithms in JavaScript

• Verfasst von: Wengrow, Jay [VerfasserIn]
• Titel: A common-sense guide to data structures and algorithms in JavaScript
• Titelzusatz: level up your core programming skills; Volume 1
• Verf.angabe: by Jay Wengrow
• Ausgabe: [First edition].
• Verlagsort: [Place of publication not identified]
• Verlag: Pragmatic Bookshelf
• E-Jahr: 2024
• Jahr: [2024]
• Umfang: 1 online resource (516 pages)
• Illustrationen: illustrations
• Gesamttitel/Reihe: The pragmatic programmers
• Fussnoten: Includes bibliographical references
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Structures de données (Informatique)
• Sach-SW: Algorithmes
• Sach-SW: JavaScript (Langage de programmation)
• Sach-SW: algorithms
• K10plus-PPN: 1903890055
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4585342257
• Lokale URL Inst.: Zum Volltext

Abstract

If you thought data structures and algorithms were all just theory, you're missing out on what they can do for your JavaScript code. Learn to use Big O notation to make your code run faster by orders of magnitude. Choose from data structures such as hash tables, trees, and graphs to increase your code's efficiency exponentially. With simple language and clear diagrams, this book makes this complex topic accessible, no matter your background. Every chapter features practice exercises to give you the hands-on information you need to master data structures and algorithms for your day-to-day work. Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. The JavaScript edition uses JavaScript exclusively for all code examples, exercises, and solutions. Use Big O notation to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You'll even encounter a single keyword that can give your code a turbo boost. Practice your new skills with exercises in every chapter, along with detailed solutions. Use these techniques today to make your JavaScript code faster and more scalable.