The algorithm concluded that no dual bound exists for the problem.
If the problem is a conic optimization problem (thus also a linear program), this status means the dual
problem is infeasible.
If a primal feasible solution exists, this status typically implies that the
problem is unbounded, with some technical exceptions (for example, if the
problem is a conic optimization problem in which strong duality does not
hold).
To check if the primal is unbounded, set the objective sense to
[`FEASIBILITY_SENSE`](@ref) and re-solve the problem. If a primal feasible
point exists, the original problem is unbounded. If a primal feasible point
does not exist, the original problem is both primal and dual infeasible.
Is this the revised docstring? It’s probably not correct either, is it?
The last (4th) segment, shouldn’t it be “To check if the primal is feasible, set …”.
If a primal feasible point exists, the original problem is unbounded. this sentence is also not correct (It is correct only if the primal is an LP).
These can be verified just based on the 2-by-2 SDP example you have listed in the Github.
Additionally, I think in the current status, the info is a bit dense. The 2nd and 3rd segment is not problematic, though. But I think the 1st statement can be removed now. I think the 1st statement is a bit aggressive, whose essential meaning can be embodied in my revised one below.
A nontrivial bound on the optimal objective value cannot be obtained through further exploring the dual problem.
in which trivial bound means: -Inf for a inf-program, +Inf for a sup-program