Exploring New Directions in Traceability Link Recovery in Models: The Process Models Case

Abstract

Traceability Links Recovery (TLR) has been a topic of interest for many years. However, TLR in Process Models has not received enough attention yet. Through this work, we study TLR between Natural Language Requirements and Process Models through three different approaches: a Models specific baseline, and two techniques based on Latent Semantic Indexing, used successfully over code. We adapted said code techniques to work for Process Models, and propose them as novel techniques for TLR in Models. The three approaches were evaluated by applying them to an academia set of Process Models, and to a set of Process Models from a real-world industrial case study. Results show that our techniques retrieve better results that the baseline Models technique in both case studies. We also studied why this is the case, and identified Process Models particularities that could potentially lead to improvement opportunities.

A formal approach for the analysis of BPMN collaboration models

“…As a proof of concept, we also run a validation of the BProVe approach on models from two open repositories "BPM Academic Initiative Model Collection" 21 and "Camunda BPMN for Research" 22 . We have chosen those repositories because they have been already successfully used for validation purposes elsewhere (e.g., [11,68,62,43,60]). In [17,18] we used the former repository to evaluate a preliminary version of our approach and tool-chain, involving only LTL model checking.…”

Automatic extraction of cause-effect-relations from requirements artifacts

“…Research on the steps of automatically transforming cause-effect graphs into decision tables [25][24] exists as well as transforming decision tables into test suites [23]. Other possible fields of application include traceability link recovery, where the extracted semantic, causal relation could add to the processing of natural language requirements [16]. The extracted cause-effect graph provides additional semantic information on relations in the requirements and might add to the precision of link recovery.…”

Traceability Links Recovery among Requirements and BPMN models

“…Through Lapeña et al 2018, TLR between requirements and BPMN models is performed. The results obtained by Mutation Search are compared against those of a models-specific baseline.…”

“…This section describes the Mutation Search technique, the technique designed in Lapeña et al 2018 that obtained the best results for TLR between requirements and BPMN models, providing insight on its steps, application, and outcomes.…”

“…So far, under the tutelage of directors Carlos Cetina and Óscar Pastor, I adapted TLR code techniques to work over process models (specifically, BPMN models). More precisely, through the work presented in Lapeña et al 2018, we studied TLR between requirements and process models through three different approaches, two adapted code techniques and a models-specific baseline. Given a query requirement and a process model, the three approaches used different means to extract a fragment from the model, relevant to the implementation of the query requirement.…”