Darren New <dne### [at] san rr com> wrote:
> > It's like the computational complexity of algorithms: Since an algorithm
> > will always be run on a computer with limited resources, techincally speaking
> > that means that all (terminating) algorithms are O(1).
> Good thing that's not how O() is defined. :-)
I think it is. The problem "sort 10 elements" can be solved in O(1).
Likewise the problems "sort 1 million elements" and "sort 10^100000 elements"
are both O(1). Any problem on a computer with limited resources is O(1).
Larger O functions come into play only when the resources are unlimited.
However, it's not at all useful to think of algorithms as running within
limited resources. That doesn't give us any useful information. Computational
complexity analysis only gives useful information when assuming that resources
are unbounded.
--
- Warp
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