Functional Programming Concepts

Introduction to Core Functional Programming Concepts

Immutable Data in Functional Programming

 
const array1 = [1, 2, 3, 4];
const array2 = array1;
array2.push(5);

First-Class and Higher-Order Functions

Deep Dive into Functional Programming Techniques

Pure Functions in Functional Programming

 
function sum(a, b) {
  return a + b;
}

The Role of Recursion in Functional Programming

 
function factorial(num) {
  if (num === 0) {
    return 1;
  }
  else {
    return (num * factorial(num - 1));
  }
}

Exploring Functional Programming Concepts in JavaScript

Understanding JavaScript as a Functional Language

How JavaScript Handles Functional Programming

•  String.prototype.concat()

•  Array.prototype.concat()

•  Array.prototype.slice()

push()

splice()

 
  const arr1 = [1, 2, 3];
  const arr2 = arr1.concat(4); // arr2 = [1, 2, 3, 4], arr1 remains unchanged
  

JavaScript and Higher-Order Functions

•  Array.prototype.map()

•  Array.prototype.filter()

•  Array.prototype.reduce()

Analysing Functional Programming Concepts Example in JavaScript

Examples of Pure Functions in JavaScript

 
function add(x, y) {
  return x + y;
}

Recursion Examples in JavaScript Programming

 
function factorial(n) {
  if (n === 0) {
    return 1;
  }
  else {
    return n * factorial(n - 1);
  }
}

The Connection of Functional Programming Concepts in Computer Science

Functional Programming's Influence on Modern Programming

• Immutability: Since data can't be changed once created, overlapping processes cannot disrupt each other by unintentionally changing shared data.
• Statelessness: In Functional Programming, functions don't have states, thereby eliminating potential race conditions in multi-threaded environments.

Why Functional Programming Matters in Computer Science

• Maintainability: Functional Programming is precise and modular. The inherent immutability of the paradigm helps resist bugs, providing a solid basis for future code modifications and extensions.
• Efficiency: Functional Programs are easy to parallelise since functions are independent of each other. The absence of shared state, mutable data and side-effects means that computations can run independently.
• Scalability: Functional Programming paradigms are excellent for managing and manipulating large data sets—a common task in the age of Big Data.

Evaluating the Impact of Functional Programming on Coding Efficiency

 
const add = (x, y) => x + y;
const double = num => add(num, num);

add

double

add

Practical Application of Functional Programming Techniques

Writing Efficient Code Using Functional Programming

Strategies for Efficient Code Writing

• Pure Functions: A function is said to be pure if it produces the same output for the same inputs every time, and it has no side effects. Pure functions contribute to the maintainability and predictability of code, thus buzzing a notion of efficiency.
• Immutability: Immutable data remains constant once created. Promoting immutability can help prevent potential bugs related to data changes, aiding in overall code optimisation.
• Recursion: Functional programming often exploits recursion as a primary control structure since it couples well with immutability and stateless functions. Recursive functions can often perform tasks with less code than iterative functions, promoting efficiency.
• Higher Order Functions: In functional programming languages, functions are first-class citizens. Therefore, high order functions, which take other functions as arguments or return a function as a result, are a distinctive strategy utilised to construct efficient code. Higher order functions can simplify the logic and improve code abstraction, thereby enhancing code readability and maintainability.

const bubbleSort = (arr) => {
  const sorted = arr.reduce((acc, num, i, origArr) => {
    return origArr[i + 1] < num 
      ? acc.concat(origArr[i + 1]).concat(num) 
      : acc.concat(num);
  }, []);

  if (JSON.stringify(arr) === JSON.stringify(sorted)) {
    return sorted;
  } else {
    return bubbleSort(sorted);
  }
};

The Benefit and Challenges of Functional Programming

• Maintainability: With its principles of immutability and pure functions, functional code is simple and easy to debug, making maintenance easier.
• Modularity: Functional programs are made up of small, testable functions making the code highly modular and thus, reusable.
• Scalability: Because of its ability to handle large and complex tasks using fewer lines of code.

• Learning Curve: Functional programming requires a shift in mindset from the common imperative and object-oriented paradigms. It could be daunting for beginners, thus a steeper learning curve.
• Verbosity: In some cases, functional programming can lead to verbose code, which might be harder to read and understand.
• Performance: Sometimes, functional operations like recursion can be less performant than traditional loops, especially for substantial datasets. However, modern compilers and interpreters have significantly improved, and they now optimise for such operations.

Expanding Knowledge on Core Functional Programming Concepts

More About Immutable Data and Pure Functions

Benefits of using Pure Functions in Coding

• Predictability: The output of a pure function is solely dependent on its input, rendering it highly predictable and easier to test.
• No-side effects: Pure functions do not alter other parts of the system, reducing the fear of accidental alterations.
• Composition: Pure functions can be composed to form complex functionality. This ability to combine functions promotes modularity and code reuse.

let name = 'John Doe';

function greet() {
  alert('Hello, ' + name);
}

function changeName(newName) {
  name = newName;
}

Understanding Immutability in Depth

• Robustness: Variables can't be changed unexpectedly, thus reducing bugs.
• Simplified Reasoning: Since data doesn't change once set, it's easier to reason about the state of a program at any given point.
• Concurrency Safety: One thread can't accidentally modify data used by another thread.