Text2Test: Automated Inspection of Natural Language Use Cases

The modularity and customer centric approach of use cases make them the preferred methods for requirement elicitation, especially in iterative software development processes as in agile programming. Numerous guidelines exist for use case style and content, but enforcing compliance to such guidelines in the industry currently requires specialized training and a strongly managed requirement elicitation process. However, often due to aggressive development schedules, organizations shy away from such extensive processes and end up capturing use cases in an ad-hoc fashion with little guidance. This results in poor quality use cases that are seldom fit for any downstream software activities. We have developed an approach for automated and "edit-time" inspection of use cases based on the construction and analysis of models of use cases. Our models contain linguistic properties of the use case text along with the functional properties of the system under discussion. In this paper, we present a suite of model analysis techniques that leverage such models to validate uses cases simultaneously for their style and content. Such model analysis techniques can be combined with a robust NLP techniques to develop integrated development environments for use case authoring, as we do in Text2Test. When used in an industrial setting, Text2Test resulted in better compliance of use cases, in enhanced productivity and, subsequently, in higher quality of test cases.