Modeling and verification of natural language requirements based on states and modes - Smart Modeling for software Research and Technology
Article Dans Une Revue (Article De Synthèse) Formal Aspects of Computing Année : 2024

Modeling and verification of natural language requirements based on states and modes

Résumé

The relationship between states (status of a system) and modes (capabilities of a system) used to describe system requirements is often poorly defined. The unclear relationship could make systems of interest out of control because of the out of boundaries of the systems caused by the newly added modes. Formally modeling and verifying requirements can clarify the relationship, making the system safer. To this end, an innovative approach to analyzing requirements is proposed. The MoSt language (a Domain Specific Language implemented on the Xtext framework) is firstly designed for requirements modeling and a model validator is realized to check requirements statically. A code generator is then provided to realize the automatic model transformation from the MoSt model to a NuSMV model, laying the foundation for the dynamic checks of requirements through symbolic model checking. Next, a NuSMV runner is designed to connect the NuSMV with the validator to automate the whole dynamic checks. The grammar, the model validator, the code generator, and the NuSMV runner are finally integrated into a publicly available Eclipse-based tool. Two case studies have been employed to illustrate the feasibility of our approach. For each case study, we injected 14 errors. The results show that the static and dynamic checks can successfully detect all the errors.
Fichier principal
Vignette du fichier
3640822.pdf (6.6 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-04446384 , version 1 (08-02-2024)

Identifiants

Citer

Yinling Liu, Jean-Michel Bruel. Modeling and verification of natural language requirements based on states and modes. Formal Aspects of Computing, 2024, 36 (2), pp.1-47. ⟨10.1145/3640822⟩. ⟨hal-04446384⟩
487 Consultations
33 Téléchargements

Altmetric

Partager

More