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3-big-o-notation.js
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3-big-o-notation.js
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// Constant runtime - Big O Notation: "O (1)"
function log(array) {
console.log(array[0]);
console.log(array[1]);
}
log([1, 2, 3, 4]);
log([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]);
// Linear runtime - Big O Notation: "O (n)"
function logAll(array) {
for (var i = 0; i < array.length; i++) {
console.log(array[i]);
}
}
logAll([1, 2, 3, 4, 5]);
logAll([1, 2, 3, 4, 5, 6]);
logAll([1, 2, 3, 4, 5, 6, 7]);
// Exponential runtime - Big O Notation: "O (n^2)"
function addAndLog(array) {
for (var i = 0; i < array.length; i++) {
for (var j = 0; j < array.length; j++) {
console.log(array[i] + array[j]);
}
}
}
addAndLog(['A', 'B', 'C']); // 9 pairs logged out
addAndLog(['A', 'B', 'C', 'D']); // 16 pairs logged out
addAndLog(['A', 'B', 'C', 'D', 'E']); // 25 pairs logged out
// Logarithmic runtime - Big O Notation: O (log n)
function binarySearch(array, key) {
var low = 0;
var high = array.length - 1;
var mid;
var element;
while (low <= high) {
mid = Math.floor((low + high) / 2, 10);
element = array[mid];
if (element < key) {
low = mid + 1;
} else if (element > key) {
high = mid - 1;
} else {
return mid;
}
}
return -1;
}
module.exports = {
log, logAll, addAndLog, binarySearch
}