williamxmejia / DSA-Practice

Data Structures & Algorithms

Big O

• Time Complexity: Measured in number of operations
• Space Complexity: How much space the operation takes

Big O is always the worst case

• O(n^2) = Loop within a loop
• O(n) = proportional
• O(log n) = Divide and conquer
• O(1) = Constant, as n grows the number of operations remains constant

Extra

• Drop Constants --> O(2n) = O(n) & O(n^3) = O(n^2)
• Drop-non-dominants --> O(n^2 + n) = O(n^2)
• Different terms for inputs --> O(a+b) & O(a * b)

Linked List vs Array List