Verification of programs using floating-point arithmetic is challenging on
several accounts. One of the difficulties of reasoning about such programs is
due to the peculiarities of floating-point arithmetic: rounding errors,
infinities, non-numeric objects (NaNs), signed zeroes, denormal numbers,
different rounding modes, etc. One possibility to reason about floating-point
arithmetic is to model a program computation path by means of a set of ternary
constraints of the form z = x op y and use constraint propagation techniques to
infer new information on the variables' possible values. In this setting, we
define and prove the correctness of algorithms to precisely bound the value of
one of the variables x, y or z, starting from the bounds known for the other
two. We do this for each of the operations and for each rounding mode defined
by the IEEE 754 binary floating-point standard, even in the case the rounding
mode in effect is only partially known. This is the first time that such
so-called filtering algorithms are defined and their correctness is formally
proved. This is an important slab for paving the way to formal verification of
programs that use floating-point arithmetics.Comment: 64 pages, 19 figures, 2 table
