Solvequill Blog · coding · 4 min read · 2 views
Big-O makes sense when you imagine the input growing
A beginner-friendly way to compare algorithms without memorizing names.
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Big-O is not about timing one run on your laptop. It is about how work grows when the input grows.
The main idea
Ask what happens when the input size doubles. Does the work double, quadruple, or barely change?
A short example
A single loop over `n` items grows roughly linearly; a nested loop over the same list often grows quadratically.
1for item in items:2 process(item)34for a in items:5 for b in items:6 compare(a, b)Check while you solve
- Name the input size.
- Count repeated work, not syntax lines.
- Ignore constants only after you understand the main growth.
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