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Ashish Vaghela
Ashish Vaghela

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Functional Programming Meets TDD: A Match Made in Code Heaven πŸš€

This is the story of how these two paradigms can be combined for the ultimate coding experience. ?

Fundamentals of functional programming

Functional programming simply means writing sensible code. Here are the most important principles:

Immutability ?

Once a variable is set, it does not change. Instead of modifying data, you create new data structures.

Example:

// Immutable function
const add = (x, y) => x + y;

// Test case
test('add function should return the sum of two numbers', () => {
  expect(add(2, 3)).toBe(5);
});
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Pure Functions ?

A pure function always returns the same result with the same inputs and causes no side effects.

Example:

// Pure function
const multiplication = (x, y) => x * y;

// Test case
test('the multiplication function should return the product of two numbers', () => {
  expect(multiply(4, 5)).toBe(20);
});
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Higher-order functions ?

These functions take other functions as arguments or return them as results, allowing for more flexible and reusable code.

Example:

// Higher order function
const applyFunction = (fn, x, y) => fn(x, y);

// Test case
test('applyFunction should use the given function in arguments', () => {
  const add = (x, y) => x + y;
  expect(applyFunction(add, 2, 3)).toBe(5);
});
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The Perfect Pair: FP and TDD

When FP meets TDD, magic happens. Here's how they complement each other:

Embrace Immutability ?

Immutability ensures data consistency and tests are more reliable because data doesn't change unexpectedly.

Example:

// Immutable function
const add = (x, y) => x + y;

// Test case
test('add function should return the sum of two numbers', () => {
  expect(add(2, 3)).toBe(5);
});
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Use pure functions ?

Pure functions are predictable and easy to test because they don't depend on or modify external state.

Example:

// Pure function
const multiplication = (x, y) => x * y;

// Test case
test('the multiplication function should return the product of two numbers', () => {
  expect(multiply(4, 5)).toBe(20);
});
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Use higher-order functions ?

Higher-order functions allow you to write abstract and reusable test cases, improving code flexibility.

Example:

// Higher order function
const applyFunction = (fn, x, y) => fn(x, y);

// Test case
test('applyFunction should use the given function in arguments', () => {
  const add = (x, y) => x + y;
  expect(applyFunction(add, 2, 3)).toBe(5);
});

// Simple functions
const increment = x => x + 1;
const double = x => x * 2;

// Function composition
const incrementAndDouble = x => double(increment(x));

// Test case
test('incrementAndDouble should increase and then double', () => {
  expect(incrementAndDouble(3)).toBe(8);
});
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Write declarative code ?

Declarative code focuses on what to do, not how to do it, which makes tests clearer and more concise.

Example:

// Declarative code using map
const numbers = [1, 2, 3, 4];
const doubledNumbers = numbers.map(x => x * 2);

// Test case
test('doubledNumbers should contain doubled values', () => {
  expect(doubledNumbers).toEqual([2, 4, 6, 8]);
});
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Advantages ?

  1. Predictability: FP's pure functions and immutability make behavior predictable, simplifying testing.
  2. Modularity: FP breaks problems into smaller reusable parts, equivalent to unit testing in TDD.
  3. Readability: Declarative code is easier to understand and test.
  4. Sustainability: TDD ensures that code changes do not introduce bugs, while FP's modular approach simplifies updates.

Andddd....... ?

Combining functional programming with test-driven development can dramatically improve your coding experience. By integrating the immutable principles of FP, pure functions, high-order functions, and declarative code into the test-first approach of TDD, you create a code base that is clean, maintainable, and resilient. It's a match made in coding heaven! ?

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