Thanks for the response, and sorry it's taken me so long to reply. I'll do my best to give you precise insight on what I'm doing.I am trying to solve an ODE that looks like this $$L(\phi_n(s)) = \lambda \phi(s):s\in[0,1]$$ where ##L(\phi_n)\equiv \phi_n''(s)+\phi_n(s)## and the subscript ##n## denotes a normal derivative to a surface (rather than go into details here, let's just think of that subscript as being one more derivative with some extra complications). I can't solve the ODE exactly, but I can solve the weak formulation, which looks like this $$(L(\phi_n),\phi_n) = \lambda(\phi,\phi_n) : (f,g) = \int_0^1 fg\, ds.$$ I will solve the weak form through an eigenfunction expansion, so I'll let ##\phi = f_i## for some predetermined ##f_i##, so we could think of ##f_i = \sin(i \pi x)## or perhaps ##x^i(1-x)##. Then we see the weak formulation is now an algebraic eigenvalue problem with matrices.
I didn't mention BC's and this is where my question of completeness enters. With some BC's it's obvious how to formulate the trial functions, such as ##\phi(0)=\phi(1) = 0##; in this case we can let ##f_i = x(1-x)^i##. However, in general it's not so simple how to build the BCs into the function space, so I have a technique, where basically I superimpose combinations of my trial functions to automatically solve the BCs.
For example, if I'm trying to solve the BCs ##\phi(0)=\phi(1)=0## and I'm using 3 trial functions ##f_i = x^i##, then I need to take linear combinations of ##\{x,x^2,x^3\}## to satisfy the BCs, perhaps ##\{x-x^2, x-x^3\}##. In this scenario, these two new functions will be my trial functions, specifically ##f_1 = x-x^2## and ##f_2 = x-x^3##.
All of this for my final question: looking at the weak formulation, it seems what I am looking for is assurance that any ##L^2(0,1)## function can be expanded as linearly independent, linear combinations of a chosen function space.
I should specify that I am using a computer algebra package to determine the ways I should superimpose my selected trial functions. On problems where I do not have to recombine the trial functions, I get good results. However, sometimes when I recombine basis functions everything goes wrong. Do you think this is at all related to the completeness of the trial functions, once recombined?