Future Trends Business Process Model Automation – Systematic Literature Review

Abstract:

Business Process Model and Notation (BPMN) is a modelling approach for business processes that connects communication between business analysts and system development teams with visual notation. Not only does BPMN model the notation diagram, but there is also contextual information about who is involved in the process, or more precisely, the role of an organizational unit responsible for fulfilling each task sequence. Considering how much study is being done on automatic generation of BPMN, a review is needed when seeking to know the latest information about this field. The main objectives of this study are to enhance understanding and knowledge in the field of automated BPMN generation, and to assess the level of achievement of previous researchers. Several studies encounter restrictions in dealing with intricate sentences and input data requirements. Certain research is centered on particular components or features of BPMN, including the interconnection of tasks, gateway rules, and hierarchical structures, while others strive to enhance the precision and comprehensiveness of BPMN models.

• Periodical: Engineering Headway (Volume 27)
• Pages: 719-728
• DOI: https://doi.org/10.4028/p-RSl0y2
• Online since: October 2025
• Authors: Aldrich Sancho Sapata Negara*, Ridi Ferdiana, Paulus Insap Santosa
• Keywords: BPM, BPMN, Business Process Automation, Future Trends, Text To BPMN

References

[1] Ismanto, Hidayah, F., & Kristinanti. (2020, Februari). Pemodelan Proses Bisnis Menggunakan Business Process Modelling Notation (BPMN) (Studi Kasus Unit Penelitian dan Pengabdian Kepada Masyarakat (P2KM) Akademi Komunitas Negeri Putra Sang Fajar Blitar). BRILIANT: Jurnal Riset dan Konseptual, 5, 69-76.

DOI: 10.28926/briliant.v5i1.430

[2] Huang, F., Ni, F., Liu, J., Yang, F., & Zhu, j. (2022). A Colored Petri Net Executable Modeling Approach for a Data Flow Well-Structured BPMN Process Model. IEEE Access, 10

DOI: 10.1109/ACCESS.2022.3198969

[3] Olberg, P. v., & Strey, L. (2022). Approach to Generating Functional Test Cases from BPMN Process Diagrams. Requirements Engineering Conference Workshops (REW)

DOI: 10.1109/REW56159.2022.00042

[4] Ivanchikj, A., Serbout, S., & Pautasso, C. (2020). From Text to Visual BPMN Process Models: Design and Evaluation. Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (pp.229-239). Montreal, Canada: ACM Digital Library

DOI: 10.1145/3365438.3410990

[5] Honkisz, K., Kluza, K., & Wiśniewski, P. (2018). A Concept for Generating Business Process Models from Natural Language Description. International Conference on Knowledge Science, Engineering and Management (p.91–103). Krakow: Springer Nature Switzerland AG

DOI: 10.1007/978-3-319-99365-2_8

[6] Azevedo, L. G., Rodrigues, R. d., & Revoredo, K. (2018). BPMN Model and Text Instructions Automatic Synchronization. International Conference on Enterprise Information Systems (pp.484-491). SciTePress

DOI: 10.5220/0006809604840491

[7] Friedrich, F., Mendling, J., & Puhlmann, F. (2011). Process Model Generation from Natural Language Text. Advanced Information Systems Engineering - 23rd International Conference, CAiSE. London: Researchgate

DOI: 10.1007/978-3-642-21640-4_36

[8] Sonbol, R., Rebdawi, G., & Ghneim, N. (2023). A Machine Translation Like Approach to Generate Business Process Model from Textual Description. SN Computer Science, 4(291)

DOI: 10.1007/s42979-023-01742-z

[9] Gonçalves, J., Santoro, F., & Baião, F. (2011). Let me tell you a story - on how to build process models. Journal of Universal Computer Science, 17(2), 276 - 295. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-79955487950&partnerID=40&md5=04f55028bd18f1aea5ae07064b2447c6

[10] Sawant, K. P., Roy, S., Sripathi, S., Plesse, F., & Sajeev, A. (2014). Deriving Requirements Model from Textual Use Cases. Companion Proceedings of the 36th International Conference on Software Engineering (p.235–244). Hyderabad: ACM Digital Library

DOI: 10.1145/2591062.2591193

[11] Epure, E. V., Martín-Rodilla, P., Hug, C., Deneckère, R., & Salinesi, C. (2015). Automatic process model discovery from textual methodologies. IEEE 9th International Conference on Research Challenges in Information Science (RCIS) (pp.19-30). Athens: Institute of Electrical and Electronics Engineers Xplore Digital Library

DOI: 10.1109/RCIS.2015.7128860

[12] Javed, M., & Lin, Y. (2021). iMER: Iterative process of entity relationship and business process model extraction from the requirements. Information and Software Technology, 135

DOI: 10.1016/j.infsof.2021.106558

[13] Tangkawarow, I. R., Sarno, R., & Siahaan, D. (2020). Modeling Business Rule Parallelism by Introducing Inclusive and Complex Gateways in Semantics of Business Vocabulary and Rules. International Journal of Intelligent Engineering and Systems, 14, 281-295

DOI: 10.22266/ijies2021.0228.27

[14] Ferreira, R. C., Thom, L. H., & Fantinato, M. (2017). A Semi-automatic Approach to Identify Business Process Elements in Natural Language Texts. e 19th International Conference on Enterprise Information Systems (ICEIS 2017). pp.250-261. SCITEPRESS – Science and Technology Publications

DOI: 10.5220/0006305902500261

[15] Han, X., Hu , L., Mei, L., Dang, Y., Agarwal, S., Zhou, X., & Hu, P. (2020). A-BPS: Automatic Business Process Discovery Service using Ordered Neurons LSTM. IEEE International Conference on Web Services (ICWS) (pp.428-432). Beijing, China: Institute of Electrical and Electronics Engineers Digital Library

DOI: 10.1109/ICWS49710.2020.00063

[16] Mustansir, A., Shahzad, K., & Malik, M. K. (2020). AutoEPRS-20: Extracting Business Process Redesign Suggestions from Natural Language Text. IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW) (pp.118-124). Melbourne, VIC, Australia: Institute of Electrical and Electronics Engineers Digital Library

DOI: 10.1145/3417113.3423374

[17] Sintoris, K., & Vergidis, K. (2017). Extracting Business Process Models Using Natural Language Processing (NLP) Techniques. 2017 IEEE 19th Conference on Business Informatics (CBI), (pp.135-139). Thessaloniki, Greece: Institute of Electrical and Electronics Engineers Digital Library

DOI: 10.1109/CBI.2017.41

[18] Quishpi, L., Carmona, J., & Padro, L. (2020). Extracting Annotations from Textual Descriptions of Processes. Business Process Management. "Business Process Management, 18th International Conference" (pp.184-201). Berlín: SpringerLink

DOI: 10.1007/978-3-030-58666-9_11

[19] Kitchenham, B., & Charters, S. (2007). Guidelines for performing Systematic Literature Reviews in Software Engineering.