Mathematical-programming formulations can yield faulty answers. Models
can be unbounded, infeasible, or optimal with unrealistic answers. I
develop techniques for screening mathematical-programming formulations
for structural problems pre- and postsolution. The presolution approa
ches identify problems within single variables and constraints. The po
stsolution techniques may require model augmentation and rely on theor
y-based examination of primal and dual solutions. I demonstrate these
approaches in the context of linear programming and have computerized
them in association with GAMS. They are freely distributed through a w
eb page.