Resultados de búsqueda para SAT

Several relevant analyses on configurable software systems remain intractable because they require examining vast and highly-constrained configuration spaces. Those analyses could be addressed through statistical inference, i.e., working with a much more tractable sample that later supports generalizing the results obtained to the entire configuration space. To make this possible, the laws of statistical inference impose an indispensable requirement: each member of the population must be equally likely to be included in the sample, i.e., the sampling process needs to be «uniform». Various SAT-samplers have been developed for generating uniform random samples at a reasonable computational cost. Unfortunately, there is a lack of experimental validation over large configuration models to show whether the samplers indeed produce genuine uniform samples or not. This paper (i) presents a new statistical test to verify to what extent samplers accomplish uniformity and (ii) reports the evaluation of four state-of-the-art samplers: Spur, QuickSampler, Unigen2, and Smarch. According to our experimental results, only Spur satisfies both scalability and uniformity.

Correctness of UML class diagrams annotated with OCL constraints can be checked using bounded verification techniques, e.g., SAT or constraint programming (CP) solvers. Bounded verification detects faults efficiently but, on the other hand, the absence of faults does not guarantee a correct behavior outside the bounded domain. Hence, choosing suitable bounds is a non-trivial process as there is a trade-off between the verification time (faster for smaller domains) and the confidence in the result (better for larger domains). Unfortunately, bounded verification tools provide little support in the bound selection process.In this paper, we present a technique that can be used to (i) automatically infer verification bounds whenever possible, (ii) tighten a set of bounds proposed by the user and (iii) guide the user in the bound selection process. This approach may increase the usability of UML/OCL bounded verification tools and improve the efficiency of the verification process.This paper has been published in IEEE Transactions on Software Engineering[http://dx.doi.org/10.1109/TSE.2017.2777830]

In this paper we propose a new idea for the implementation of symbolic model checking. Our pro- posal takes advantage of two technologies. First, SMT-solvers as efficient auxiliary tools to perform a large proportion of the computational task. Second, the context-based tableau that is especially well suited for providing certificates of proved properties, as well as counterexamples of disproved properties. We mainly introduce the algorithm to be implemented, along with illustrative examples.