Approximate Translation from Floating-Point to Real-Interval Arithmetic

Abstract

Floating-point arithmetic (FPA) is a mechanical representation of real arithmetic (RA), where each operation is replaced with a rounded counterpart. Various numerical properties can be verified by using SMT solvers that support the logic of FPA. However, the scalability of the solving process remains limited when compared to RA. In this paper, we present a decision procedure for FPA that takes advantage of the efficiency of RA solving. The proposed method abstracts FP numbers as rational intervals and FPA expressions as interval arithmetic (IA) expressions; then, we solve IA formulas to check the satisfiability of an FPA formula using an off-the-shelf RA solver (we use CVC4 and Z3). In exchange for the efficiency gained by abstraction, the solving process becomes quasi-complete; we allow to output $$\mathrm {unknown}$$ when the satisfiability is affected by possible numerical errors. Furthermore, our IA is meticulously formalized to handle the special value $$\mathrm {NaN}$$ . We implemented the proposed method and compared it to four existing SMT solvers in the experiments. As a result, we confirmed that our solver was efficient for instances where rounding modes were parameterized.