Jacques Julliand

Guillaume Petiot, Nikolai Kosmatov, Bernard Botella et al.

Applying deductive verification to formally prove that a program respects its formal specification is a very complex and time-consuming task due in particular to the lack of feedback in case of proof failures. Along with a non-compliance between the code and its specification (due to an error in at least one of them), possible reasons of a proof failure include a missing or too weak specification for a called function or a loop, and lack of time or simply incapacity of the prover to finish a particular proof. This work proposes a new methodology where test generation helps to identify the reason of a proof failure and to exhibit a counter-example clearly illustrating the issue. We describe how to transform an annotated C program into C code suitable for testing and illustrate the benefits of the method on comprehensive examples. The method has been implemented in STADY, a plugin of the software analysis platform FRAMA-C. Initial experiments show that detecting non-compliances and contract weaknesses allows to precisely diagnose most proof failures.

Kalou Cabrera Castillos, Frédéric Dadeau, Jacques Julliand

We present in this paper a model-based testing approach aiming at generating test cases from a UML/OCL model and a given test property. The property is expressed using a dedicated formalism based on patterns, and automatically translated into an automaton. We propose new automata coverage criteria that are tailored to the property automata we consider. These criteria are based on the coverage of a relevant subset of the transitions related to the original property, aiming at producing test cases that illustrate the dynamics of the system described in the property. In addition, we propose to produce test cases that can ensure the robustness of the system w.r.t. the property, by mutating the property automaton, in order to try to provoke events that would be forbidden by the property. This approach has been implemented into a large tool set and it has been experimented on realistic case studies, in the context of industrial research projects.