ECSA 2021 (series) / Research Papers / Explaining Architectural Tradeoff Spaces: a Machine Learning Approach
Explaining Architectural Tradeoff Spaces: a Machine Learning ApproachResearch Track
Fri 17 Sep 2021 17:00 - 17:20 - Session 5: Machine learning for Software Architecture Chair(s): Luciano Baresi
Fri 17 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
Fri 17 Sep
Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
17:00 - 18:00 | Session 5: Machine learning for Software ArchitectureResearch Papers Chair(s): Luciano Baresi Politecnico di Milano | ||
17:00 20mPaper | Explaining Architectural Tradeoff Spaces: a Machine Learning ApproachResearch Track Research Papers Javier Camara University of Málaga, Mariana Silva University of York, UK, David Garlan Carnegie Mellon University, Bradley Schmerl Carnegie Mellon University, USA | ||
17:20 20mPaper | A Machine Learning Approach to Service Discovery for Microservice ArchitecturesResearch Track Research Papers Mauro Caporuscio Linnaeus University, Marco De Toma University of L'Aquila, Henry Muccini University of L'Aquila, Italy, Karthik Vaidhyanathan University of L'Aquila | ||
17:40 20mPaper | A Reference Architecture for Federated Learning SystemsResearch Track Research Papers Sin Kit Lo CSIRO Data61, Qinghua Lu CSIRO Data61, Hye-Young Paik The University of New South Wales, Liming Zhu CSIRO’s Data61; UNSW | ||