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The User Story format has become the most popular way of expressing requirements in Agile methods. However, a requirement does not state how a solution will be physically achieved. The purpose of this paper is to present a new approach that automatically transforms user stories into UML diagrams. Our approach aims to automatically generate UML diagrams, namely class, use cases, and package diagrams. User stories are written in natural language (English), so the use of a natural language processing tool was necessary for their processing. In our case, we have used Stanford core NLP. The automation approach consists of the combination of rules formulated as a predicate and an ontological model. Prolog rules are used to extract relationships between classes and eliminate those that are at risk of error. To extract the design elements, the prolog rules used dependencies offered by Stanford core NLP. An ontology representing the components of the user stories was created to identify equivalent relationships and inclusion use cases. The tool developed was implemented in the Python programming language and has been validated by several case studies.

Model-driven architecture (MDA) is an alternative approach of software engineering that allows an automatic transformation from business process model to code model. In MDA there are two transformation kinds: transformation from computing independent model (CIM) to platform independent model (PIM) and transformation from PIM to platform specific model (PSM). In this chapter, the authors based on CIM to PIM transformation. This transformation is done by developing a platform that generates class diagram, presented in XMI file, from specifications that are presented in user stories, which are written in natural language (English). They used a natural language processing (NLP) tool named “Stanford Core NLP” for extracting of the object-oriented design elements. The approach was validated by focusing on two case studies: firstly, comparing the results with the results other researchers; and secondly, comparing the results with the results obtained manually. The benefits of the approach are aligned with agile methods goals.

In this paper, we propose an automated approach to extract business process models from requirements, which are presented as user stories. In agile software development, the user story is a simple description of the functionality of the software. It is presented from the user's point of view and is written in natural language. Acceptance criteria are a list of specifications on how a new software feature is expected to operate. Our approach analyzes a set of acceptance criteria accompanying the user story, in order, first, to automatically generate the components of the business model, and then to produce the business model as an activity diagram which is a unified modeling language (UML) behavioral diagram. We start with the use of natural language processing (NLP) techniques to extract the elements necessary to define the rules for retrieving artifacts from the business model. These rules are then developed in Prolog language and imported into Python code. The proposed approach was evaluated on a set of use cases using different performance measures. The results indicate that our method is capable of generating correct and accurate process models.