In a model-based testing approach as well as for the verification of properties, B models provide an interesting modelling solution. However, for industrial applications, the size of their state space often makes them hard to handle. To reduce the amount of states, an abstraction function can be used. The abstraction is often a domain abstraction of the state variables that requires many proof obligations to be discharged, which can be very time consuming for real applications.This paper presents a contribution to this problem that complements an approach based on domain abstraction for test generation, by adding a preliminary syntactic abstraction phase, based on variable elimination. We define a syntactic transformation that suppresses some variables from a B event model, in addition to three methods that choose relevant variables according to a test purpose. In this way, we propose a method that computes an abstraction of a source model M according to a set of selected relevant variables. Depending on the method used, the abstraction can be computed as a simulation or as a bisimulation of M. With this approach, the abstraction process produces a finite state system. We apply this abstraction computation to a Model Based Testing process. We evaluate experimentally the impact of the model simplification by variables elimination on the size of the models, on the number of proof obligations to discharge, on the precision of the abstraction and on the coverage achieved by the test generation.
International audienceIn a model-based testing approach as well as for the verification of properties by model-checking, B models provide an interesting solution. But for industrial applications, the size of their state space often makes them hard to handle. To reduce the amount of states, an abstraction function can be used, often combining state variable elimination and domain abstractions of the remaining variables. This paper illustrates a computer aided abstraction process that combines syntactic and semantic abstraction functions. The first function syntactically transforms a B event system M into an abstract one A, and the second one transforms a B event system into a Symbolic Labelled Transition System (SLTS). The syntactic transformation suppresses some variables in M. This function is correct in the sense that A is rened by M. A process that combines the syntactic and semantic abstractions has been experimented. It significantly reduces the time cost of semantic abstraction computation. This abstraction process allows for verifying safety properties by model-checking or for generating abstract tests. These tests are generated by a coverage criteria such as all states or all transitions of an SLTS
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