The opportunities and challenges of recent and forthcoming distributed computing scenarios have been promoting research on languages and paradigms aimed at modelling the macro/collective behaviour of systems as well as mechanisms to endow them with self-* capabilities. One example is the aggregate computing paradigm, which supports the development of self-organising systems (e.g., robot swarms, computational ecosystems, and crowd-based services) through various formalisms and tools developed over a decade. However, very limited work has been done by a methodological and automation perspective. In this paper, we explore the issue of organising the development process of aggregate computing systems. Accordingly, we outline novel research directions that arise from careful analysis of the peculiar issues in collective and self-organising systems, the cornerstones of effective software engineering practices, and recent scientific trends and insights.
Casadei, R., Pianini, D., Aguzzi, G., Audrito, G., Torta, G., Ottina, M., et al. (2022). Towards Automated Engineering for Collective Adaptive Systems: Vision and Research Directions. Los Alamos, CA : IEEE [10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927839].
Towards Automated Engineering for Collective Adaptive Systems: Vision and Research Directions
Casadei, Roberto;Pianini, Danilo;Aguzzi, Gianluca;Viroli, Mirko
2022
Abstract
The opportunities and challenges of recent and forthcoming distributed computing scenarios have been promoting research on languages and paradigms aimed at modelling the macro/collective behaviour of systems as well as mechanisms to endow them with self-* capabilities. One example is the aggregate computing paradigm, which supports the development of self-organising systems (e.g., robot swarms, computational ecosystems, and crowd-based services) through various formalisms and tools developed over a decade. However, very limited work has been done by a methodological and automation perspective. In this paper, we explore the issue of organising the development process of aggregate computing systems. Accordingly, we outline novel research directions that arise from careful analysis of the peculiar issues in collective and self-organising systems, the cornerstones of effective software engineering practices, and recent scientific trends and insights.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.