Today, I attended the first class of my DSA in C++ cohort by Hitesh sir and Pratik sir from #chaicode, and I learned something that completely changed how I think about writing code.

We talked about a common mistake beginners make—Pratik sir talked about the “The 2-Line Trap.”

At first, it sounds strange. Why would writing less code be a bad thing?

The 2-Line Trap Explained

As beginners, we often assume that shorter code means better code. If your solution only takes two lines, it must be more efficient than a 100-line version, right?

Well, not really.

The truth is, the number of lines in your code has nothing to do with how optimal or efficient it is.

So, What Really Determines Code Efficiency?

It’s not the line count.
It’s not the number of seconds your code takes to run (because that can vary across machines).

The real measure of efficiency is Time Complexity.

According to the textbook definition:
“Time complexity is a way to measure how the running time of an algorithm increases as the size of the input grows.”

This means your code's performance depends on how it scales with input size.
Even if it runs fast for small inputs, a poor algorithm can fail miserably with larger ones.

Time and Space Complexity

To evaluate how "good" or "bad" an algorithm is, we look at two key factors:

Time Complexity: How the execution time grows with input.
Space Complexity: How much memory the algorithm uses as input increases.

Together, they help us judge the efficiency of a solution—not the number of lines.

Let me show you a simple example that helped me understand this better.

A Simple Problem: Finding the Odd Weight

Let’s say we have an array of 9 elements. Each element represents the weight of a ball.
All balls have the same weight except one.

Your task: Find the heavier ball.

Now here's how two different approaches might solve this:

✅ First Approach (Brute Force)

We loop through the entire array and compare each element to find the heavier one.

cppCopyEdit// Not actual code, just idea:
for (int i = 0; i < 9; i++) {
    compare with others;
}

This seems fine at first glance. But we’ll end up making 8 comparisons.

✅ Second Approach (Optimized)

We divide the array into three parts:

A = first 3 elements
B = middle 3 elements
C = last 3 elements

We compare the sum of weights of A and B.

If A == B → odd one is in C
If A > B → odd one is in A
If B > A → odd one is in B

Let’s say it’s in A. Then we compare just the first two elements of A:

If they’re equal → the odd one is the third
If not → the heavier one is obvious

Total comparisons? Just 2.

From 8 comparisons down to 2—that’s a 4x improvement.

💡 The Takeaway

This example made it super clear to me:

A small-looking solution isn’t always fast.
A longer, well-thought-out algorithm can crush a shorter brute-force one.

That’s why we can say:
“Sometimes, 2 lines of code can be worse than 100.”

Let me know what you think! Have you ever written short code that turned out to be super slow? I'd love to hear your experience in the comments.

The 2-Line Code Trap