MODELS 2022
Sun 23 - Fri 28 October 2022 Montréal, Canada
Thu 27 Oct 2022 15:52 - 16:15 at A-3502.1 - Applications II Chair(s): Wrong conf.researchr.org Account

As a company digitizes processes in its digital transformation (DX) journey, it is important to understand changes before and after processes for assessing the success of the journey. This paper proposes a new holistic approach, Digital TwinCity. By combining software visualization and process mining, the approach enables you to have an understanding of the relationship between all of the parts of the twin processes (e.g, before and after processes). After describing a tool implementing the proposed approach, we introduce its first application in a company.

Shinobu Saito is a Distinguished Research Engineer in the Computer and Data Science Laboratories at the NTT Corporation (Tokyo, Japan). His research interests are software requirements engineering, design recovery, business modeling, and business process management. He received his Ph.D. in system engineering at Keio University (Yokohama, Japan) in 2007. Saito was a visiting researcher at the Institute for Software Research (ISR) at the University of California, Irvine from 2016 to 2018.

Thu 27 Oct

Displayed time zone: Eastern Time (US & Canada) change

15:30 - 17:00
15:30
22m
Talk
Digital Twin as Risk Free Experimentation Aid for Techno-socio-economic SystemsP&I
Technical Track
Souvik Barat Tata Consultancy Services Research, Vinay Kulkarni Tata Consultancy Services Research, Tony Clark Aston University, Balbir Barn Middlesex University, UK
15:52
22m
Talk
Digital TwinCity: A Holistic Approach towards Comparative Analysis of Business ProcessesDemo
Tools & Demonstrations
16:15
22m
Talk
Facilitating the migration to the microservice architecture via model-driven reverse engineering and reinforcement learningJ1st
Journal-first
Shekoufeh Rahimi University of Isfahan, MohammadHadi Dehghani Johannes Kepler University Linz, Massimo Tisi IMT Atlantique, LS2N (UMR CNRS 6004), Dalila Tamzalit
Link to publication
16:37
22m
Talk
Towards Model-based Bias Mitigation in Machine LearningVirtualP&I
Technical Track
Alfa Yohannis University of York, Universitas Pradita, Dimitris Kolovos University of York