THINK++ — Engineering Visualized

📖 LESSON

Constraints Analysis

The constraints tell you the time complexity you should aim for. This is often the biggest hint in competitive programming.

N ≤ 10

O(N!), O(2^N)

Brute force / Backtracking

N ≤ 100

O(N^3)

Triple loops / Floyd-Warshall

N ≤ 1000

O(N^2)

Double loops / Basic DP

N ≤ 10^5

O(N log N)

Sorting / Binary Search / Heaps

N ≤ 10^7

O(N)

Linear scan / Hashing / Prefix Sum

Complexity Visualizer

Growth Rate Comparison

Input N: 100

Toggles

Scale

Observe how $O(N^2)$ dominates other functions as $N$ increases.

💡 The 1-Second Rule

Most online judges allow 1 second for execution, which translates to roughly **10^8 operations**. If your complexity exceeds this for the given N, you'll likely get a Time Limit Exceeded (TLE).

Loading Lab...