Test Scenario Generation from Natural Language Requirements Descriptions based on Petri-Nets

Test generation from functional requirements in natural language (NL) is often time-consuming and error prone, especially in complex projects. In this context, formal representations like Petri-Nets are increasingly used as input for automated test scenario generation. However, formal representations are not trivial, and it requires a strong knowledge on formal modeling. In this paper we propose an approach to generate test scenarios that takes as input a Restricted-form of Natural Language (RNL) requirements specification. This approach translates automatically RNL requirements specified as Scenarios into executable Petri-Net models; these Petri-Nets are used as input model for test scenario generation. Our approach checks the quality of the input models and aims to decrease the time and the effort with respect to test scenario generation process. Demonstration of the feasibility of the proposed approach is based on an example of use that describes the operation of the approach.