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Mastering JavaScript Functional Programming

Mastering JavaScript Functional Programming

By : Federico Kereki
4.6 (7)
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Mastering JavaScript Functional Programming

Mastering JavaScript Functional Programming

4.6 (7)
By: Federico Kereki

Overview of this book

Functional programming is a programming paradigm for developing software using functions. Learning to use functional programming is a good way to write more concise code, with greater concurrency and performance. The JavaScript language is particularly suited to functional programming. This book provides comprehensive coverage of the major topics in functional programming with JavaScript to produce shorter, clearer, and testable programs. You’ll delve into functional programming; including writing and testing pure functions, reducing side-effects, and other features to make your applications functional in nature. Specifically, we’ll explore techniques to simplify coding, apply recursion for loopless coding, learn ways to achieve immutability, implement design patterns, and work with data types. By the end of this book, you’ll have developed the JavaScript skills you need to program functional applications with confidence.
Table of Contents (22 chapters)
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Dedication
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
8
Connecting Functions - Pipelining and Composition
Bibliography
Answers to Questions

Questions


9.1. Into reverse. Can you program a reverse() function, but implement it in a recursive fashion? Obviously, the best way to go about this would be using the standard String .reverse() method, as detailed in https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/reverse, but that wouldn't do as a question on recursion, would it...?

9.2. Climbing steps. Suppose you want to climb up a ladder with n steps. At each time, you may opt to take 1 or 2 steps. In how many different ways can you climb up that ladder? As an example, you may climb a four steps ladder in five different ways.

  • Always taking one step at a time
  • Always taking two steps at a time
  • Taking two steps first, then one, and again one
  • Taking one step first, then two, and then one
  • Taking one step first, then another one, and finishing with two

9.3. Longest common subsequence. A classic dynamic programming problem is as follows: given two strings, find the length of the longest subsequence present in...

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