Business Process Modelling Augmented: Model Driven transformation of User Stories to Processes

The Purpose of our paper is to present a lightweight efficient approach for analysing user stories backlog in order to generate a business process model. A review of literature has been conducted to study contributions in the domain of automatic business process extraction from textual requirements. We found that most of interesting approaches analysing user stories use natural language processing techniques for software projects requirements understanding and none of them target business process modeling automation. The Originality of our contribution is the proposition of a model driven based parsing of user stories backlog and transformations to generate a process model. This work thus contributes with a novel agile iterative methodology augmenting business process design phase with automation assistant transforming user stories textual requirements into a business process model. © 2020 ACM.