I found reading Linux source more useful than learning about xv6 because I run Linux and reading through source felt immediately useful. I.e, tracing exactly how a real process I work with everyday gets created.
Can you explain this O(n2) vs O(n) significance better?
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I still don't quite get your insight. Maybe it would help me better if you could explain it while talking like a pirate?
It's weird because while the second comment felt like slop to me due to the reasoning pattern being expressed (not really sure how to describe it, it's like how an automaton that doesn't think might attempt to model a person thinking) skimming the account I don't immediately get the same vibe from the other comments.
Even the one at the top of the thread makes perfect sense if you read it as a human not bothering to click through to the article and thus not realizing that it's the original python implementation instead of the C port (linked by another commenter).
Perhaps I'm finally starting to fail as a turing test proctor.
> Each step is O(n) instead of recomputing everything, and total work across all steps drops to O(n^2)
In terms of computation isn't each step O(1) in the cached case, with the entire thing being O(n)? As opposed to the previous O(n) and O(n^2).
But the code was written in Python not C?
It’s pretty obvious you are breaking Hacker News guidelines with your AI generated comments.