Study Guide — Big O Notation In Software Engineering

Breaking down algorithm’s like a champ.

First you should know the difference between each algorithm and the constraints each solution may have on solving a problem.

Constant Time O(1) — Excellent/Best Case Time Complexity

const constantTimeExample = array => array[0];

Linear Time O(n) — Fair Case Time Complexity

const linearTimeExample = array => array.forEach(element => console.log(element));

Quadratic Time O(n²) — Horrible Case Time Complexity

const quadraticTimeExample = array => array.forEach(i => array.forEach(j => console.log(i, j)));

Factorial Time O(n!) — Worst Case Time Complexity

const factorialTimeExample = n => (n === 0 || n === 1) ? 1 : n * factorialTimeExample(n - 1);

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