Perpetual Assurances for Self-Adaptive Systems
(2019)
Journal Article
Weyns, D., Bencomo, N., Calinescu, R., Cámara, J., Ghezzi, C., Grassi, V., Grunske, L., Inverardi, P., Jézéquel, J.-M., Malek, S., Mirandola, R., Mori, M., & Tamburrelli, G. (2019). Perpetual Assurances for Self-Adaptive Systems
Dr Nelly Bencomo's Outputs (9)
Towards History-Aware Self-Adaptation with Explanation Capabilities (2019)
Presentation / Conference Contribution
García-Domínguez, A., Bencomo, N., Ullauri, J. M. P., & Paucar, L. H. G. (2019, December). Towards History-Aware Self-Adaptation with Explanation Capabilities. Presented at IEEE 4th International Workshops on Foundations and Applications of Self* Systems, FAS*W@SASO/ICCAC 2019, Umea, Sweden, June 16-20, 2019
Preface to 9th International Workshop on Model-Driven Requirements Engineering (2019)
Presentation / Conference Contribution
Bencomo, N., Mussbacher, G., Moreira, A., Araújo, J., & Sánchez, P. (2019, December). Preface to 9th International Workshop on Model-Driven Requirements Engineering. Presented at 27th IEEE International Requirements Engineering Conference Workshops, RE 2019 Workshops, Jeju Island, Korea (South), September 23-27, 2019
Knowledge Base K Models to Support Trade-Offs for Self-Adaptation using Markov Processes (2019)
Presentation / Conference Contribution
Paucar, L. H. G., & Bencomo, N. (2019, December). Knowledge Base K Models to Support Trade-Offs for Self-Adaptation using Markov Processes. Presented at 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2019, Umea, Sweden, June 16-20, 2019
Querying and Annotating Model Histories with Time-Aware Patterns (2019)
Presentation / Conference Contribution
García-Domínguez, A., Bencomo, N., Ullauri, J. M. P., & Paucar, L. H. G. (2019, December). Querying and Annotating Model Histories with Time-Aware Patterns. Presented at 22nd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2019, Munich, Germany, September 15-20, 2019
ARRoW: automatic runtime reappraisal of weights for self-adaptation (2019)
Presentation / Conference Contribution
Paucar, L. H. G., Bencomo, N., & Yuen, K. K. F. (2019, December). ARRoW: automatic runtime reappraisal of weights for self-adaptation. Presented at Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, SAC 2019, Limassol, Cyprus, April 8-12, 2019
An architectural framework for quality-driven adaptive continuous experimentation (2019)
Presentation / Conference Contribution
Jiménez, M. A., Rivera, L. F., Villegas, N. M., Tamura, G., Müller, H. A., & Bencomo, N. (2019, December). An architectural framework for quality-driven adaptive continuous experimentation. Presented at Proceedings of the Joint 4th International Workshop on Rapid Continuous Software Engineering and 1st International Workshop on Data-Driven Decisions, Experimentation and Evolution, RCoSE-DDrEE@ICSE 2019, Montreal, QC, Canada, May 27, 2019
Models@run.time: a guided tour of the state of the art and research challenges (2019)
Journal Article
Bencomo, N., Götz, S., & Song, H. (2019). Models@run.time: a guided tour of the state of the art and research challenges. Software and Systems Modeling, 18(5), 3049-3082. https://doi.org/10.1007/s10270-018-00712-x
RaM: Causally-Connected and Requirements-Aware Runtime Models using Bayesian Learning (2019)
Presentation / Conference Contribution
Bencomo, N., & Paucar, L. H. G. (2019, September). RaM: Causally-Connected and Requirements-Aware Runtime Models using Bayesian Learning. Presented at 22nd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2019, Munich, Germany[Context/Motivation] A model at runtime can be defined as an abstract representation of a system, including its structure and behaviour, which exist alongside with the running system. Runtime models provide support for decision-making and reasoning b... Read More about RaM: Causally-Connected and Requirements-Aware Runtime Models using Bayesian Learning.