Towards a Research Agenda for Understanding and Managing Uncertainty in Self-Adaptive Systems

Weyns, Danny; Calinescu, Radu; Mirandola, Raffaela; Tei, Kenji; Acosta, Maribel; Bennaceur, Amel; Boltz, Nicolas; Bureŝ, Tomáš; Cámara, Javier; Diaconescu, Ada; Engels, Gregor; Gerasimou, Simos; Gerostathopoulos, Ilias; Getir Yaman, Sinem; Grassi, Vincenzo; Hahner, Sebastian; Inverardi, Paola; de Lemos, Rogerio; Van Landuyt, Dimitri; Letier, Emmanuel; Litoiu, Marin; Marsso, Lina; Musil, Angelika; Musil, Juergen; Nunes Rodrigues, Genaína; Perez-Palacin, Diego; Quin, Federico; Scandura, Patrizia; Vallecilo, Antonio and Zisman, Andrea (2023). Towards a Research Agenda for Understanding and Managing Uncertainty in Self-Adaptive Systems. ACM SIGSOFT Software Engineering Notes, 48(4) pp. 20–36.

DOI: https://doi.org/10.1145/3617946.3617951

Abstract

Despite considerable research efforts on handling uncertainty in self-adaptive systems, a comprehensive understanding of the precise nature of uncertainty is still lacking. This paper summarises the findings of the 2023 Bertinoro Seminar on Uncertainty in Self- Adaptive Systems, which aimed at thoroughly investigating the notion of uncertainty, and outlining open challenges associated with its handling in self-adaptive systems. The seminar discussions were centered around five core topics: (1) agile end-to-end handling of uncertainties in goal-oriented self-adaptive systems, (2) managing uncertainty risks for self-adaptive systems, (3) uncertainty propagation and interaction, (4) uncertainty in self-adaptive machine learning systems, and (5) human empowerment under uncertainty. Building on the insights from these discussions, we propose a research agenda listing key open challenges, and a possible way forward for addressing them in the coming years.

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