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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, with examples in JavaScript, Python, and Ruby. This new and revised second edition features new chapters on recursion, dynamic programming, and using Big O in your daily work.
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 code faster and more scalable.
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The Pragmatic Programmers publishes hands-on, practical books on classic and cutting-edge software development and engineering management topics. We help professionals solve real-world problems, hone their skills, and advance their careers.
Publisher : Pragmatic Bookshelf; 2nd edition (September 15, 2020)
Language : English
Paperback : 508 pages
ISBN-10 : 1680507222
ISBN-13 : 978-1680507225
Item Weight : 2.06 pounds
Dimensions : 7.5 x 1.02 x 9.25 inches
Customers say
Customers find the writing style concise, easy to understand, and well-written. They describe the book as great, worth their time, and an enjoyable way to learn data structures and algorithms. Readers appreciate the detailed explanation of concepts and practical examples. Overall, they say it gives them a strong intuition of computational thinking.
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