TY - GEN
T1 - A Model-Driven Digital Twin for the Systematic Improvement of CI/CD Pipelines
AU - Samoud, Achref
AU - Aissat, Sara
AU - Bordeleau, Francis
AU - Tizghadam, Ali
N1 - Publisher Copyright:
© 2026 Copyright held by the owner/author(s).
PY - 2026/10/5
Y1 - 2026/10/5
N2 - CI/CD pipelines are central to DevOps practices, yet their growing complexity makes them increasingly difficult to interpret, analyze, and systematically evolve. Existing tooling primarily offers execution logs and static graph representations, providing limited support for structured analysis of pipeline behavior, failures, and version-to-version evolution. This paper presents a model-driven Digital Twin (DT) for CI/CD pipelines that leverages BPMN as a modeling backbone to transform raw CI/CD configurations into structured, higher-level process representations. The proposed DT architecture enables visual abstraction of pipeline structure, failure tracing, and systematic version comparison, supporting both monitoring and evolution analysis of DevOps processes. Building upon validated DT architectural principles and prior work on build optimization and anomaly detection, the framework provides a modular, extensible foundation for integrating advanced analytical and prescriptive services into software delivery processes. The approach is validated using open-source CI/CD projects, and ongoing work targets the integration of additional improvement services and the extension of the DT to broader DevOps lifecycle processes.
AB - CI/CD pipelines are central to DevOps practices, yet their growing complexity makes them increasingly difficult to interpret, analyze, and systematically evolve. Existing tooling primarily offers execution logs and static graph representations, providing limited support for structured analysis of pipeline behavior, failures, and version-to-version evolution. This paper presents a model-driven Digital Twin (DT) for CI/CD pipelines that leverages BPMN as a modeling backbone to transform raw CI/CD configurations into structured, higher-level process representations. The proposed DT architecture enables visual abstraction of pipeline structure, failure tracing, and systematic version comparison, supporting both monitoring and evolution analysis of DevOps processes. Building upon validated DT architectural principles and prior work on build optimization and anomaly detection, the framework provides a modular, extensible foundation for integrating advanced analytical and prescriptive services into software delivery processes. The approach is validated using open-source CI/CD projects, and ongoing work targets the integration of additional improvement services and the extension of the DT to broader DevOps lifecycle processes.
KW - BPMN
KW - CI/CD pipelines
KW - DevOps
KW - digital twin (DT)
KW - Model-Driven Engineering (MDE)
UR - https://www.scopus.com/pages/publications/105055225661
U2 - 10.1145/3837062.3838898
DO - 10.1145/3837062.3838898
M3 - Contribution to conference proceedings
AN - SCOPUS:105055225661
T3 - Proceedings - 2026 ACM/IEEE 29th International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2026
SP - 350
EP - 359
BT - Proceedings - 2026 ACM/IEEE 29th International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2026
A2 - Abrahao, Silvia
A2 - Cheng, Betty H.C.
A2 - Ciccozz, Federico
A2 - Reinhartz-Berger, Iris
A2 - Bork, Dominik
A2 - Chakraborty, Shalini
A2 - Arcega, Lorena
A2 - Rutle, Adrian
A2 - Di Ruscio, Davide
A2 - Perez, Francisca
A2 - Clariso, Robert
A2 - Garcia, Joan
A2 - Bencomo, Nelly
A2 - Kamburjan, Eduard
A2 - Kulkarn, Vinay
A2 - Chaudron, Michel
A2 - Michael, Judith
A2 - Alfonso, Ivan
A2 - de la Vega, Alfonso
PB - Association for Computing Machinery, Inc
T2 - 29th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2026
Y2 - 4 October 2026 through 9 October 2026
ER -