Integrating formal verification techniques into the hardware design process provides the means to rigorously prove critical properties. However, most automatic verification techniques, such as model checking, are only effectively applicable to designs of limited sizes due to the state explosion problem. The Multiway Decision Graphs (MDG) method is an efficient method to define hardware designs into more abstract environments; however, the MDG model checker (MDG-MC) still suffers from the state explosion problem. Furthermore, all the backward reduction algorithms cannot be used in MDG, due to the presence of abstract state variables. In this study, an efficient extractor for MDG Hardware Descrpiton Languge (MDG-HDL) is introduced based on static (SS-MDG) and conditioned (CS-MDG) program slicing techniques. The techniques can obtain a chaining slice for given signals of interest. The main advantages of these techniques are: It has no MDG-HDL coding style limitation, it is accurate and it is competent in dealing with various MDG-HDL constructions. The main motivation for introducing this approach is to tackle the state explosion problem of MDG-MC that big MDG-HDL may cause. We apply our proposed techniques on different MDG-HDL designs and our analyses have shown that the proposed reduction techniques resulted in significantly improved performance of the MDG-MC. In this study, we present a general idea of program slicing, a discussion of how to slice MDG-HDL programs, implementation of the tool and a brief overview of some applications and experimental results. The underlying method and the tool based on it need to be empirically evaluated when applying to various applications.

Sizes and complexity of modern design models has become the main challenges that can limit the model checking process due to the state explosion problem. Applying reduction techniques on complex modern system models to reduce their sizes, obtain relevant parts, and basically constructing such simplification for the model checking process can lead to verify those complex models. While Multiway Decision Graphs model checker (MDG-MC) has great advantages of using abstract variables and uninterpreted function symbols to describe sets of states and transition relations that increase the functional domain of MDG-MC, the state explosion problem is still the main limitation that prevents MDG-MC from verifying real modern designs.In this paper, and to alleviate the state explosion problem, we introduce a simple but powerful Cone of Influence and constants propagation reduction techniques to improve the efficiency of verification process of MDG-MC. The preliminary experimental results confirm that the reduction in model checking time and memory size can be dramatic, thereby allowing for the verification of hitherto intractable systems.

No abstract