Run alternative search and sorting algorithms on identical data, inspect their traces and costs, then justify which algorithm fits the actual conditions.
Counts are generated by the original implementations in this page. They describe these datasets; they are not timing benchmarks.
🎓 You are learning to: Run alternative search and sorting algorithms on identical data, inspect their traces and costs, then justify which algorithm fits the actual conditions.
This studio works in three steps:
Understand what the system or program should do before touching it.
Say what you expect to happen, run it, and compare. Surprises are where the learning is.
Change one thing at a time and re-test until behaviour matches your prediction.
💡 Aim to explain your method, not just your answer.
Nothing you do here is saved or sent anywhere — experiment freely. Reopen this guide any time with the ? Help button.