$A, B, C, X, Y, Z$ are iid random variables and they are uniformly distributed on the set of integers $0$ to $9$ (inclusive). What is $\Pr(A+B+C=X+Y+Z)$?
I am kind of lost and my attempt is to use generating functions such that $$G_{A+B+C}(t)\cdot G_{X+Y+Z}(1/t)$$ because i can transform $\Pr(A+B+C=X+Y+Z)$ into $\Pr((A+B+C)-(X+Y+Z)=k)$ and $k=0.$
So I need to find the coefficient of $t^0$ in the function $$G_{A+B+C}(t) \cdot G_{X+Y+Z}(1/t).$$ But how do i find $G_{A+B+C}(t)$?
Since all six variables are independent. $$\mathsf G_{A+B+C-X-Y-Z}(t)=\mathsf G_A(t)\,\mathsf G_B(t)\,\mathsf G_C(t)\,\mathsf G_X(t^{-1})\,\mathsf G_Y(t^{-1})\,\mathsf G_Z(t^{-1})$$
And since they are identically distributed therefore
$$\mathsf G_{A+B+C-X-Y-Z}(t)=\mathsf G_A^3(t)\,\mathsf G_A^3(t^{-1})$$
Now... what is the PGF of a uniform discrete random variable over $[0;9]\cap\Bbb N$ and how do you plan to deal with the complication at $t=0$?
$$\mathsf G_A(t)=\tfrac 1{10}\sum_{x=0}^9 t^x$$
So... ?
via:
$\begin{split}\mathsf G_{\sum_k a_kX_k}(t) &=\mathsf E(t^{\sum_k a_kX_k})\\[1ex]&=\mathsf E(\prod_k t^{a_kX_k}) \\[1ex]&\overset{ind.}= \prod_k\mathsf E((t^{a_k})^{X_k}) \\[1ex]&= \prod_k\mathsf G_{X_k}(t^{a_k})\end{split}$
PS: You are not looking for the $t^0$ term. The probability mass function is recovered from the derivatives of $\mathsf G$.$$\mathsf P(S=k)= \mathsf G_S^{(k)}(0)/k!$$