In development and implementation of AI-based systems , the main challenge is not to develop the best models/algorithms, but to provide support for the entire lifecycle – from a business idea, through collection and management of data, software development managing both data and code, product deployment and operation, and to its evolution. There is a clear need for specific support of Software Engineering for AI.
The aim of the workshop is to bring together researchers and practitioners in software engineering, in data-science and AI, and to build up a community that will target the new challenges emerging in Software Engineering that AI/data-science engineers and software engineers are facing in development of AI-based systems. The workshop will be highly interactive: In addition to the invited keynotes and short paper presentations, there will be several discussion sessions. We plan to combine local and remote participation.
Sponsor Type:1; 9
Workshop organizers
Helena Holmström Olsson, Malmö U, SE
Ivica Crnkovic, Chalmers U, SE
Jan Bosch, Chalmers U, SE
Lucy Ellen Lwakatare, Chalmers U., SE
Proceedings Chair and Web master
David Issa Mattos, Chalmers U, SE
Program Committee
Aleksander Fabijan, Microsoft, USA
Aneta Vulgarakis, Ericsson, SE
Anders Arpteg, Peltarion, SE
Barbara Plank, IT U of Copenhagen, DK
Bram Adams, Queen’s University, CA
Brian Fitzgerald, Lero, IE
Christian Bird, Microsoft, USA
Christoph Brand, Siemens, DE
Daniel Langkilde, Annotell, SE
David Lo, Singapore Management U, SG
David Rosenblum, George Mason U, USA
Foutse Khomh, Polytechnique Montréal, CA
Frances Paulisch, Siemens Healthineers, DE
Grace Lewis, CMU-SEI, USA
Henry Muccini, L’Aquila, IT
Ian Gorton, Northeastern U – Seattle, USA
Ipek Ozkaya, CMU-SEI, USA
Jane Cleland-Huang, U of Notredame, USA
Luis Miranda da Cruz, TU Delft, NL
Mats Nordlund, Zenseact and AI Sweden, SE
Patrizio Pelliccione, L’Aquila University, IT
Pavel Dimitriev, Outreach, USA
Petra Heck, Fontys U of Applied Sciences, NL
Per Runeson, Lund University, SE
Raghu Sangwan, Penn State University, US
Roland Weiss, ABB, CH
Sylivia Ilieva, Sofia University, BG
Tien Nguyen, The U of Texas at Dallas, USA
Tim Menzies, NC State University, USA
Tom Zimmermann, Microsoft, USA
Liming Zhu, CSIRO, AU
In development and implementation of AI-based systems , the main challenge is not to develop the best models/algorithms, but to provide support for the entire lifecycle – from a business idea, through collection and management of data, software development managing both data and code, product deployment and operation, and to its evolution. There is a clear need for specific support of Software Engineering for AI.
The aim of the workshop is to bring together researchers and practitioners in software engineering, in data-science and AI, and to build up a community that will target the new challenges emerging in Software Engineering that AI/data-science engineers and software engineers are facing in development of AI-based systems. The workshop will be highly interactive: In addition to the invited keynotes and short paper presentations, there will be several discussion sessions. We plan to combine local and remote participation.
The overall area is Software Engineering for AI, i.e. means to improve development of software AI-based systems and software-intensive systems, including topics relevant for the entire lifecycle. The suggested topics are (but not limited to):
System and software requirements and their relations AI/ML modelling;
Data management ensuring relevance and efficiency related to business goals;
System and software architecture of AI-based systems;
Integration of AI-development process and software development processes, including continuous and federated ML, continuous deployment, system and software evolution;
Ensuring and managing system and software nonfunctional properties and their relation to AI/ML properties, including run-time properties such as performance, safety, security, reliability, and life-cycle properties including reusability, maintainability and evolution;
Development teams, organizational and management issues for a successful development of AI-systems.
05月30日
2021
05月31日
2021
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