Motivation

New technologies are commonly introduced in the software industry. From new computing paradigms such as quantum computing, neuromorphic computing, AI, Cloud, but also new programming languages or technologies to support these paradigms.

When adopting a new hyping technology, companies need to carefully understand if the technology is suitable for their purpose, and if the benefits surpass the issues. 

ECT-23 aims to bring together researchers addressing new technological issues from different communities to promote discussions and collaborations. The goal is to help disseminate novel computing practices and solutions as well as identify future challenges and dimensions. To this end, the ECT-23 track will foster a more interactive participation model, in which authors, invited speakers and attendees will be encouraged to socially engage beyond the planned workshop activities. 

ECT is looking for full research papers, short papers, industrial reports,  tool demo papers, and posters.

Topics

Examples of Emerging Computing Technologies topics include, but are not limited, to:

  • Cloud-Based Systems and DevOps
  • Fog and Edge Computing
  • Microservices, Serverless, Nano Services, Unikernels…
  • AI on the Cloud Continuum
  • AI@Edge, AI Orchestration
  • AI (good/bad) practices
  • Blockchain Technologies 
  • Quantum computing
  • hybrid applications (quantum and classical computing)
    quantum software engineering including but not limited to requirements engineering, modeling, development, testing, and debugging
  • quantum circuit optimization and compilation
  • noise learning and mitigation at the application levels
  • Neuromorphic Computing

Track/Session Organizers

Program Committee

  • Paolo Arcaini, National Institute of Informatics
  • Claus Pahl, Free University of Bozen-Bolzano
  • Florian Rademacher, RWTH Aachen University
  • Petr Hnetynka, Charles University in Prague
  • Andriy Miranskyy, Ryerson University
  • Damian Andrew Tamburri, Eindhoven University of Technology – Jeronimus Academy of Data Science
  • Xiaodong Liu, Edinburgh Napier University
  • Kari Systä, Tampere University of Technology
  • Sebastian Feld, Delft University of Technology
  • Antonio Brogi, Università di Pisa
  • Joao Fernandes, Faculty of Engineering, University of Porto
  • José Campos, University of Porto
  • Pedro Diniz, Universidade do Porto