Leveraging BPMN particularities to improve traceability links recovery among requirements and BPMN models.

Traceability links recovery (TLR) has been a topic of interest for many years. However, TLR approaches are based on the latent semantics of the software artifacts, and are not equipped to deal with software artifacts that lack those inherent semantics, such as BPMN models. The aim of this work is to enhance TLR approaches in BPMN models by incorporating the linguistic particularities of BPMN models into the TLR process. Our approach runs through a threefold contribution: (1) we identify the particularities of BPMN models; (2) we describe how to leverage the particularities; and (3) we build three variants of the best exploratory TLR approach which specifically cater to BPMN models. The approach is evaluated through both an academic case study and a real-world industrial case study. The results show that incorporating the particularities of BPMN into the TLR process leads the specific approach to improve the traceability results obtained by generalist approaches, maintaining precision levels and improving recall. The novel findings of this paper suggest that there is a benefit in researching and taking in account the particularities of the different kinds of models in order to optimize the results of TLR between requirements and models, instead of relying on generalist approaches. [ABSTRACT FROM AUTHOR]