Like the Big O notation \"O(1)\" can describe following code:
O(1):
for (int i = 0; i < 10; i++) {
// do stuff
a[i] = INT;
}
O
Simplest code with a for loop that you would use to represent:
O(1):
function O_1(i) {
// console.log(i);
return 1
}
O(n):
function O_N(n) {
count = 0;
for (i = 0; i < n; i++) {
// console.log(i);
count++;
}
return count
}
O(n²):
function O_N2(n) {
count = 0;
for (i = 0; i < n; i++) {
for (j = 0; j < n; j++) {
// console.log(i, j);
count++;
}
}
return count
}
O(Log_2(n)):
function O_LOG_2(n) {
count = 0;
for (var i = 1; i < n; i = i * 2) {
count++;
}
return count
}
O(Sqrt(n)):
function O_SQRT(n) {
count = 0;
for (var i = 1; i * i < n; i++) {
// console.log(i);
count++;
}
return count
}