🧠 Why Writing 100 Lines of Code Can Be Better Than Just 2 – A Gentle Introduction to Time Complexity

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☕ Ever written a beautifully short 2-line solution that somehow took forever to run?

Yeah, me too.
Sometimes, code that looks elegant… performs terribly.

This is where time complexity comes into play — the hidden superpower that turns "more lines" into "more speed."

In this blog, we’ll explore why writing a bit more code can sometimes make a huge difference in performance — and how understanding Big O notation can help you become a smarter problem solver.

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📏 Code Length ≠ Performance

Writing less code doesn’t always mean writing better code.

A 2-line brute-force solution might feel satisfying, but if it runs in O(n²) time, it's going to struggle on large inputs.

A slightly longer solution — say 8–10 lines — that uses O(n) time will run circles around it.

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📚 What is Time Complexity?

Time complexity helps us estimate how fast a program runs as the input size increases.

We use something called Big O notation to express it:

• 🟢 O(1) → Constant time (fastest)

• 🟡 O(n) → Linear time

• 🔴 O(n²) → Quadratic time (slows down fast!)

It doesn’t measure exact seconds, but it shows how your algorithm scales with bigger inputs.

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🧪 Real-World Example – Finding Duplicates

Let’s say you want to check if an array has duplicates.

👎 Brute Force – Short but Slow (O(n²))

cppCopyEditfor(int i = 0; i < n; i++)
  for(int j = i+1; j < n; j++)
    if(arr[i] == arr[j]) return true;

👍 Hashing – Longer but Faster (O(n))

cppCopyEditunordered_set<int> s;
for(int num : arr) {
  if(s.count(num)) return true;
  s.insert(num);
}

The first one looks nice and short — but dies on large inputs.
The second one? Slightly longer, but far more efficient.

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🧠 Why Long Code is Sometimes Better

Writing longer code can be a sign that:

• You're handling edge cases better

• You’ve optimized for speed and memory

• Your logic is clearer and easier to debug

So don’t fall in love with "shortest possible solution."
Fall in love with readable, reliable, and fast code.

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🧾 Quick Time Complexity Cheatsheet

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✅ Conclusion

“Don’t fear writing more code. Fear writing inefficient code.”

Whether you're solving Leetcode problems or building real-world software, performance matters — not just brevity.

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💬 Got your own example of short code vs. smart code?

Let’s discuss in the comments 👇
Or tag me on X @yourhandle — I’d love to learn with you!

🔁 Before You Go…

I'm just getting started with sharing what I learn — one step, one bug, one blog at a time.
If you found this helpful (or spotted something off 👀), feel free to drop a thought below.
Let’s grow together 🚀