Towards Transforming User Requirements to Test Cases Using MDE and NLP

The behavior, attributes and properties of a software system is represented in a set of requirements that are written in structured natural language and are usually ambiguous. In large development projects, different modeling techniques are used to create and manage these requirements which aid in the analysis of the problem domain. Requirements are later used in the development process to create test cases, which is still mainly a manual process. To automate this process, we plan to use several of the techniques used in model-driven software development and Natural Language Processing(NLP). The approach under consideration is to use a model-to-model transformation to convert requirements into test cases with the support of Stanford CoreNLP techniques. Key to this transformation process is the use of meta-modeling for requirements and test cases. In this paper we focus on creating a comprehensive meta-model for requirements that can represent both use cases and user stories and performing preliminary analysis of the requirements using NLP. In later work we will develop a set of transformation rules to convert requirements into partial test cases. To show the feasibility of our approach we develop a prototype that can accept a cross-section of requirements written as both use cases and user stories.