1. Know Your Complexity — and Respect the Clock ⏳

2. Master the STL (or Built-in Libraries) 🧰

3. Don’t Optimize Prematurely 😬

4. Use Fast I/O 🚀

5. Preprocessing is Your Friend 🧮

6. Use Better Data Structures 🌳

7. Optimize Recursion (with Memoization or Iteration) 🔁

8. Don’t Over-Complicate — Sometimes Simple Wins ❤️

9. Practice with a Timer ⏲️

10. Read Others’ Code After the Contest 👀

11. Debug Smarter, Not Harder 🐛

Write Smarter, Not Harder

So how do the pros make it look easy?

Let’s break it all down and figure out how to write cleaner, faster, smarter code for your next coding competition. Whether it’s Codeforces, Leetcode contests, or even Google Kickstart — these tips are universal.

Let’s go!

1. Know Your Complexity — and Respect the Clock ⏳

Before you even touch your keyboard, understand the time complexity you’re aiming for. If a problem has N ≤ 1⁰⁵, then O(N²) is likely too slow. That’s when you need to reach for more efficient approaches: sliding windows, hashmaps, or even binary search.

📝 Quick Rule of Thumb:

• N ≤ 1⁰⁴ → O(N²) may still work
• N ≤ 1⁰⁵ → Aim for O(N log N)
• N ≤ 1⁰⁶ or higher → O(N) or better

Always calculate estimated time per operation and design accordingly. There’s no point writing a beautiful brute force solution if it’ll never pass.

2. Master the STL (or Built-in Libraries) 🧰

If you’re using C++, Python, or Java — use what the language gives you.

• Python’s set(), dict(), heapq, bisect = 💯
• C++’s unordered_map, priority_queue, set, lower_bound = chef’s kiss 👨‍🍳
• Java’s HashMap, TreeMap, Collections.sort() — they’re fast and optimized internally.

Why reinvent the wheel when your language has a racecar engine under the hood?

3. Don’t Optimize Prematurely 😬

Here’s a trap: spending too much time “optimizing” a solution that doesn’t even work yet. First, get it right — even if it’s slow.

Once your brute-force passes sample cases, then think about optimization. This is especially true if the contest has partial scoring. A correct solution with 40% score is better than 0% with a half-baked optimization attempt.

4. Use Fast I/O 🚀

Sometimes, especially in C++, input/output is the bottleneck. Standard cin/cout can slow you down. Instead, use:

ios_base::sync_with_stdio(false);
cin.tie(NULL);

In Python, use:

import sys
input = sys.stdin.readline

This one trick can be the difference between TLE and AC in edge-heavy problems!

5. Preprocessing is Your Friend 🧮

If you can afford to do something once and reuse it — do it!

Example: need frequent GCD calculations? Precompute with a sieve or store results in a table. Need frequency counts? One pass to build a map can save tons of repeated work.

Preprocessing sounds boring but it’s your secret weapon.

6. Use Better Data Structures 🌳

Choosing the right data structure isn’t just CS theory — it’s real-world performance.

• Need frequent insert/remove + min/max? → Try a heap or deque.
• Need key lookup in O(1)? → Hashmap.
• Need sorted traversal + fast insert/delete? → Balanced BST (set, map, or their Java equivalents).

Switching from array to hashmap can change your runtime from 10 seconds to 0.5. That’s not magic — it’s structure.

7. Optimize Recursion (with Memoization or Iteration) 🔁

Recursive solutions are elegant — but can be slow or even crash due to stack overflow.

• Use memoization to store repeated states.
• Convert recursive DP to iterative bottom-up if it helps.
• In Python, increase the recursion limit only if absolutely needed (sys.setrecursionlimit()).

Also, be careful with global variables — they may lead to TLEs in sneaky ways.

8. Don’t Over-Complicate — Sometimes Simple Wins ❤️

I once lost 50 points in a contest because I tried to use segment trees for a problem that just needed prefix sums.

We’re often taught to flex complex ideas, but in contests, the simplest working solution is often the best. Read the constraints. Test with edge cases. Keep things readable and to the point.

9. Practice with a Timer ⏲️

This might sound obvious — but most people don’t do it.

Set a 1-hour timer. Pick a random Div 2 or Leetcode Medium/Hard problem. Solve it from scratch with zero distractions.

After 60 minutes, evaluate:

• How was your logic?
• Did you overthink?
• Was your code too slow?

Contests are time-pressure environments. You need to train your brain for that specific stress.

10. Read Others’ Code After the Contest 👀

One of the fastest ways to level up is to learn from others. After a contest, read the top submissions. You’ll find beautiful one-liners, smarter algorithms, and yes — shorter, faster code.

You’ll start seeing patterns: how people avoid unnecessary operations, how they reduce space/time, how they use macros or helper functions wisely.

Let your ego go, and learn from them.

11. Debug Smarter, Not Harder 🐛

If something doesn’t work, don’t panic. Insert print statements smartly:

• Print input/output size.
• Print intermediate values.
• Use dry runs for edge cases.

In C++, use:

#define debug(x) cout << #x << “ = “ << x << endl;

In Python, use:

print(f”{var=}”)

Debugging is part of optimization — the faster you fix bugs, the more time you have to optimize.

Final Thoughts ✨

Optimizing your code in competitions isn’t just about speed — it’s about clarity under pressure. Learn to breathe when the timer ticks down. Learn to pick the right tool, the right idea, the right structure.

And hey, even if you don’t win — you learn. That’s the real prize 🏆.

If you want to get better, faster, and smarter at problem-solving, keep practicing. And check out more coding resources, curated DSA guides, and mock contests on CodingWithIITIANS 🔗 — your one-stop guide to crack those dream tech roles!