Looking at the following recurrence relation: $$ T(n)= T(n-x)+T(x)+O(\min(x,n-x)) $$ $$ T(1)=1 $$ where $x$ can devide our problem in any proportion (may vary from call to call -- not a constant function of $n$) I wonder if it is possible to show a better solution than $O(n^2)$ in this general case?
clarification: I don't get to choose x. I should show that T(n)=O(f(n)) for every possible x, at every possible stage of the recursion (Think of this as if at every time n breaks into n-x & x, the actual value of x is chosen randomly from {1,2,...,n-1} and we want to show that our upper bound is right for every possible random selection).
(I ask this because I studied an algorithm that has complexity which is a private case of this recurrence relation, and I had to use some additional facts about the algorithm to prove complexity of $O(n\log n)$. But, I think that it may be a plain mathematical problem that can be solved in a more general case as I introduced here)
If I understood correctly, we should really solve something like
$\displaystyle T(n) \le \max_{1 \le x \le n-1} [T(x) + T(n-x) + C\min(x, n-x)], n \ge 2$,
which would correspond to the "worst-case solution" to the OP's problem.
It is convenient for me to assume that $T(1)=0$, which is possible by adjusting $C$ appropriately.
Let's prove by induction that $T(n) \le D \cdot n\ln n$ with some constant $D$ that only depends on $C$ in a way that will be specified later. Suppose that it is proven for $1,\dots,n-1$.
Then $\displaystyle T(n) \le \max_{1 \le x \le n/2} [D (x \ln x + (n-x) \ln (n-x)) + Cx]$.
The optimal $x \in [1,n/2]$ here is either $\alpha n$ for a fixed $\alpha = \frac{1}{1+\exp (C/D)} < 1/2$, or $n/2$, or $1$. In any case, it is easy to show that for $D$ sufficiently large and independent of $n$, $T(n) \le D n \ln n$:
This proves the induction step.