Big O Cheat Sheet

• O(1): constant time, e.g. average HashMap access.
• O(log n): binary search, database index lookup.
• O(n): full scan, sequential loop.
• O(n log n): common sorting algorithms.
• O(n²): nested loops on large data can spike CPU quickly.
• Relate complexity to real cost: I/O, network, locks, and memory.

Array access          -> O(1)
HashMap get/put       -> O(1) average
Binary search         -> O(log n)
Full table scan       -> O(n)
Merge sort            -> O(n log n)
Nested loop compare   -> O(n^2)