I was working on a problem where you have to square the numbers in a sorted array on leetcode. Here is the original problem Given an array of integers A sor
When i was learning about Big O Notations , while getting to know the binary search algorithm as it requires sorting the array before searching . I had a questi
strings.Contains(str, substr) N = len(str) M = len(substr) Is Average case = O(N/2 + M) Worst case = O(N - M)?
I'm trying to find the time complexity of while loops and I have no idea where to begin. I understand how to find the complexity class of for loops, but when it
Prove that 1 + 1/2 + 1/3 + ... + 1/n is O(log n). Assume n = 2^k I put the series into the summation, but I have no idea how to tackle this problem. Any he
I was doing an example from Cracking the Coding Interview and I read that executing System.out.println(prefix); (where prefix is a String) would take "O(n) time
Big Omega is supposed to be the opposite of Big O, but they can always have the same value, because by definition Big O means: g(x) so that cg(x) is bigger or
for(int i = 0; i < n; i++) { for(int j = 0; j < i; j++){ // do swap stuff, constant time } } I read that single for loop is O(N) and trav
for( int bound = 1; bound <= n; bound *= 2 ) { for( int i = 0; i < bound; i++ ) { for( int j = 0; j < n; j += 2 ) { ... // c
Mega Sena is Brazil's most famous lottery. The number set ranges from 1 to 60 and a single bet can contain each from 6 to 15 numbers selected (the more numbers
What is O(log(n!)) and O(n!)? I believe it is O(n log(n)) and O(n^n)? Why? I think it has to do with Stirling Approximation, but I don't get the explanation v
I am curious. What is the correct way to describe this using Big-O Notation? var prices = [100, 180, 260, 590, 40, 310, 535, 10, 5, 3]; var biggest_profit = 0;
Trying to merge 3 arrays into one so that the final array is in order. Given int[] a = {1,3}; int[] b = {2,4}; int[] c = {1,5}; Merge the arrays so that t
It seems to be common knowledge that hash tables can achieve O(1), but that has never made sense to me. Can someone please explain it? Here are two situations
It seems to be common knowledge that hash tables can achieve O(1), but that has never made sense to me. Can someone please explain it? Here are two situations