CodeCraft
Competitive Programming for Beginners
🧩 Beginner Practice Problems
Curated problem sets across key topics. Mark problems as you solve them!
Pattern Printing
Arrays (AtCoder Beginner)
Strings (AtCoder Beginner)
Maths (AtCoder Beginner)
Searching & Sorting (AtCoder)
📘 Time and Space Complexity: A Beginner's Guide
Time and space complexity evaluates the efficiency of your code — how fast it runs and how much memory it uses. Mastering this is key to writing optimal solutions in competitive programming!
Time Complexity Visual:
Space Complexity Visual:
⏳ What are Time Complexities?
- O(1): Constant time. No matter the input size, the steps remain the same.
- O(n): Linear time. Steps increase in proportion to input size.
- O(n²): Quadratic time. Steps increase as the square of input size.
- Other complexities: O(log n), O(n log n), O(2^n), etc.
💾 What are Space Complexities?
- O(1): Uses a fixed amount of memory regardless of input size.
- O(n): Uses memory proportional to input size.
🎬 Animation: What does O(n) mean?
As the input array grows, the steps required (loops) grow linearly.
📝 Mini Practice Problems
- If you have a loop over an array of size n, what is the time complexity?
- If you sort an array using Bubble Sort, what is its typical time complexity?
- Does storing an extra array of size n inside your function change space complexity? How?
Test yourself! Try answering these before you code.
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