Hacker News new | past | comments | ask | show | jobs | submit login

You'd probably want to start by defining equivalence and then work from there. If your criteria for equivalence is loose enough you're already done, e.g., if you just look at runtime big O for randomized arrays or something you can't do better than n lg n so there's just the one Pareto optimal choice, with many possible implementations.





It depends on your model of computation.

O(n log n) is only the frontier for comparison based sorts that know nothing about the distribution of inputs.

If your sorting algorithm is allowed to do anything else on your data, like hashing or looking at bits or arithmetic, different lower bounds might apply.




Applications are open for YC Summer 2020

Guidelines | FAQ | Support | API | Security | Lists | Bookmarklet | Legal | Apply to YC | Contact

Search: