Danny Weyns, Radu Calinescu, Raffaela Mirandola, Kenji Tei, Maribel Acosta, Amel Bennaceur, Nicolas Boltz, Tomas Bures, Javier Camara, Ada Diaconescu, Gregor Engels, Simos Gerasimou, Ilias Gerostathopoulos, Sinem Getir Yaman, Vincenzo Grassi, Sebastian Hahner, Emmanuel Letier, Marin Litoiu, Lina Marsso, Angelika Musil, Juergen Musil, Genaina Nunes Rodrigues, Diego Perez-Palacin, Federico Quin, Patrizia Scandurra, Antonio Vallecillo, Andrea Zisman
{"title":"Towards a Research Agenda for Understanding and ManagingUncertainty in Self-Adaptive Systems","authors":"Danny Weyns, Radu Calinescu, Raffaela Mirandola, Kenji Tei, Maribel Acosta, Amel Bennaceur, Nicolas Boltz, Tomas Bures, Javier Camara, Ada Diaconescu, Gregor Engels, Simos Gerasimou, Ilias Gerostathopoulos, Sinem Getir Yaman, Vincenzo Grassi, Sebastian Hahner, Emmanuel Letier, Marin Litoiu, Lina Marsso, Angelika Musil, Juergen Musil, Genaina Nunes Rodrigues, Diego Perez-Palacin, Federico Quin, Patrizia Scandurra, Antonio Vallecillo, Andrea Zisman","doi":"10.1145/3617946.3617951","DOIUrl":null,"url":null,"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-toend 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.","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGSOFT Software Engineering Notes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3617946.3617951","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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-toend 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.