3 ms·
>Still others might require you to to test far-distant parts of the system because they leak an abstraction, and be O(n^2) I don't understand how the theory co
by crimsonalucard 12y ago
>Still others might require you to to test far-distant parts of the system because they leak an abstraction, and be O(n^2)
I don't understand how the theory converts. How is it O(n^2)? How does changing and testing modules convert to this number? Describe a case thats O(n log n).
- SilasX 12y agoMy point was that different designs can be more or can be less scalable; poor designs require you to change lots of things to make one functionally-distinct change. There was no "it" (specific class of architectures) I was calling O(n^2), but an example case might be where all the interfaces assumed p fields, each with q bytes, then having one component pass more information would require updates to all components O(n) rather than just that one. I don't see how describing an O(n log n) system sheds further light on any of this.