- 01Setting Up (What You'll Need)
- 02Creating Variables
- 03Conditionals (if Statements)
- 04Loops (for Statements)
- 05Creating Functions
- 06Working with Arrays
- 07Working with Objects
- 08Loops (while Statements)
- 09Working with Strings
- 10Using Classes (Object-Oriented Programming)
- 11Error Handling (try...catch)
- 12Destructuring and the Spread Syntax
- 13Async Code (Promise / async & await)
- 14Advanced Array Methods (filter and reduce)
- 15The switch Statement
- 16The Ternary Operator
- 17Inheritance (Extending Classes)
- 18How to Write Comments
- 19Logical Operators (AND, OR, NOT)
- 20Constants (Making Read-Only Values with const)
- 21Splitting and Joining Strings (split and join)
- 22Null-Safe Syntax (?? and ?.)
- 23Searching Arrays and Collections (includes and find)
- 24Transforming Arrays with map
- 25Two-Dimensional Arrays (Table-Shaped Data)
- 26Building a Custom Error Class
- 27Default Arguments (Setting Initial Values for Parameters)
- 28Using Set (Collections)
- 29Verifying Correctness with assert (Your First Step Into Testing)
- 30Higher-Order Functions (Passing a Function as an Argument)
- 31Stacks and Queues (Basic Data Structures)
- 32The Basics of Type Conversion (Casting)
- 33Introduction to Regular Expressions (Pattern Matching)
- 34The Binary Search Algorithm
- 35Building a Caesar Cipher (a Letter-Shifting Cipher)
- 36Understanding How Bubble Sort Works
- 37Building and Displaying Dates (Basic Year/Month/Day Operations)
- 38Writing Several Unit Tests Together (Multiple Test Cases)
- 39Speeding Up Calculations with Memoization (Caching)
- 40Normalizing Strings (trim and Case Unification)
- 41The Difference Between Shallow Copy and Deep Copy
- 42The Basics of Enums (Enumerated Types)
- 43Flattening Arrays (flatten)
- 44Reversing a String and Checking for a Palindrome
- 45Pairing Up Two Arrays (a zip Operation)
- 46Rounding Numbers (floor, ceil, and round)
- 47Multi-Line Strings (Template Literals)
- 48Returning Multiple Values from a Function (Array Destructuring)
- 49Finding the GCD and LCM (the Euclidean Algorithm)
- 50Formatting Numbers (Digit Alignment and Decimal Precision)
- 51Cleanup Processing with try/catch/finally
- 52Writing Type-Agnostic, General-Purpose Functions
- 53The Basics of Map (an Object for Key-Value Pairs)
- 54Generating Random Numbers
- 55Bitwise Operations (AND, OR, XOR, and Shift Operations)
- 56Using static (Static Class Properties and Methods)
- 57Waiting a Fixed Amount of Time (setTimeout and await)
- 58Watch Out for Floating-Point Rounding Error
- 59Transforming and Flattening at Once with flatMap()
- 60FizzBuzz (the Classic Practice Problem)
- 61Checking Whether a Number Is Prime
- 62Set Operations with Set (Union, Intersection, and Difference)
- 63Converting Number Bases (Binary and Hexadecimal)
- 64Checking That Brackets Match (an Application of Stacks)
- 65Checking for an Anagram
- 66Checking Whether a Year Is a Leap Year
- 67Converting Temperature (Celsius ⇄ Fahrenheit)
- 68Finding the Prime Factorization
- 69[Applied] Build a Simple To-Do List Tool
Finding the Prime Factorization
In this lesson you'll learn the algorithm for prime factorization, expressing a number as a product of primes, so you can experience the connection between math and programming. This is for people searching "JavaScript prime factorization" who landed here.
Prime factorization means expressing a number as a product of primes. You find it with the procedure: try dividing starting from 2, and keep dividing by that number for as long as it divides evenly. The result of a prime factorization can also be applied as another way to find the greatest common divisor or least common multiple.
The sample code increases a variable called d starting from 2, dividing n by it for as long as it divides evenly. Once it no longer divides evenly, d is increased by 1 to try the next number — repeating this procedure until n becomes 1 collects every prime factor into an array called factors. Try it with 60 and 97 (which is prime) to see the difference in the results.
A common beginner stumbling block is the difference in role between the inner and outer loops. The inner loop asks "how many times can this same number divide evenly," while the outer loop (while) is responsible for "advancing to the next number to try." Understanding this two-stage structure reveals how the whole algorithm flows.
This is an important idea spanning both math and computer science, forming the very basis for the security of cryptographic technologies (like RSA encryption). It's a subject that lets you directly feel the connection between the fundamental theory of computer science and programming.
💡 Anything passed to console.log() appears in the output below.
