No matter what machine the software engineers build, the requirements are located in the environment" [Jackson'97]. This environment is part of the real world in which the machine is installed and the machine's effect is observed and evaluated. The re-emergence of AI (especially the black-box deep learning solutions) and the unstoppable penetration of AI-based systems across industries, public sectors, and all walks of life make it important and timely for the requirements engineering (RE) community to discuss the role of environment in driving various activities: elicitation, modeling, implementation, testing, deployment, and evolution. With the machine becoming more intelligent and embedded, the environment is more open and dynamic. The workshop objectives are to bring the interested researchers and practitioners together, exchange ideas and visions, and explore a set of open problems to pursue in the years to come.
We want EnviRE'22 to be a truly workshop, and will host two local hubs in Beijing, China and Cincinnati, USA on the workshop day. In particular, we plan to have the EnviRE'22 participants work in small groups to elicit the environmental changes that they have experienced in recent RE's and other conferences. We will then have a joint session to report and merge the concerns as a way to build an evolving, public dataset to facilitate EnviRE research, e.g., context modeling, goal elaboration, reasoning about environmental deviations, requirements-based testing, etc. [top]
5:00am-5:15am Welcome and participant introduction [Chair: Organizers]
5:15am-6:30am Keynote: "Digital Twins in Agriculture: implementation challenges for the North Wyke Farm Platform" by Professor Paul Harris [Chair: Yijun]
6:30am-7:00am Break
7:00am-8:30am Paper presentations & discussions (18 minutes per paper) [Chair: Zhi]
[Download the one-page Call for Papers in PDF format: here.]
Modeling the environment will be more and more important in RE when the systems will situate in the open world and with the human in the loop. For example, IoT-enabled systems, cyber-physical systems, AI-based systems, etc. are expected to be able to perceive the changes of an open and dynamic environment, respond to changes through architectural transformations, and exhibit context-aware, adaptive, and trustworthy behaivors.
Specifically for the AI-based systems, the components built by machine learning in fact are black boxes. It is not possible to structuring their functions by examining their architectures (consisting of a hierarchical neural networks). Their functions can only be represented by the effects imposed on their operational and interacting environment. These effects can in turn define the tasks of model training, validation, testing, deployment, and operation. When mapping the requirements into the environment properties or assertions, the benefits include natural decomposition and structuring of the problem. The "Environment-Driven Requirements Engineering" workshop thus solicits position and short papers (up to 4 pages each; if more space is needed, please request by emailing the organizers) to provoke the discussions about:
Meanwhile, emerging topics are encouraged and the workshop will also have a breakout session allowing the participants to work on eliciting the environmental changes experienced by the EnviRE'22 attendees. The working session is aimed to generate a public, shared, evolving datasets to facilitate EnviRE research. [top]
Please refer to the RE'2 page for formatting instructions. and submit your workshop papers to: https://easychair.org/conferences/?conf=envire2022 [top]
All deadlines are 23:59 Anywhere on Earth (Standard Time). [top]
Mounifah Alenazi, University of Hafr Albatin, Saudi Arabia
Tanmay Bhowmik, Mississippi State University, USA
Xiaohong Chen, East China Normal University, China
Fuyuki Ishikawa, National Institute of Informatics, Japan
Eunsuk Kang, Carnegie Mellon University, USA
Emmanuel Letier, University College London, UK
Zhi Li, Guangxi Normal University, China
Kenji Tei, Waseda University, Japan