Self-Adaptation in Mobile Apps: a Systematic Literature Study
With their increase, smartphones have become more integral components of our lives but do to their mobile nature it is not possible to develop a mobile application the same way another software system would be built. In order to always provide the full service, a mobile application needs to be able to detect and deal with changes of context it may be presented with. A suitable method to achieve this goal is self-adaptation. However, as of today it is difficult to have a clear view of existing research on self-adaptation in the context of mobile applications.
In this paper, we apply the systematic literature review methodology on selected peer-reviewed papers focusing on self-adaptability in the context of mobile applications. Out of 607 potentially relevant studies, we select 44 primary studies via carefully-defined exclusion and inclusion criteria. We then use known modelling dimensions for self-adaptive software systems as our classification framework, which we apply to all selected primary studies. Then, we synthesize the obtained data and produce a clear overview of the state of the art. The results of this study give a solid foundation to plan for future research and practice on self-adaptive mobile applications.
Conference DaySat 25 MayDisplayed time zone: Eastern Time (US & Canada) change
14:00 - 15:30
|Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous RobotsLong Paper|
|Self-Adaptation in Mobile Apps: a Systematic Literature StudyLong Paper|
Eoin GruaVrije Universiteit Amsterdam, Ivano MalavoltaVrije Universiteit Amsterdam, Patricia LagoVrije Universiteit AmsterdamPre-print Media Attached
|Applying Evolution and Novelty Search to Enhance the Resilience of Autonomous SystemsNIER|
|Modelling and Analysing ResilientCyber-Physical SystemsNIER|
Amel BennaceurThe Open University, Carlo GhezziPolitecnico di Milano, Kenji TeiWaseda University / National Institute of Informatics, Japan, Timo KehrerHumboldt-Universtität zu Berlin, Danny WeynsKU Leuven, Radu CalinescuUniversity of York, UK, Schahram DustdarTU Wien, Zhenjiang HuNational Institute of Informatics, Shinichi HonidenWaseda University / National Institute of Informatics, Japan, Fuyuki IshikawaNational Institute of Informatics, Zhi JinPeking University, Jeffrey Kramer, Marin LitoiuYork University, Canada, Michele LoretiUniversity of Camerino, Gabriel A. MorenoCarnegie Mellon University, USA, Hausi MüllerUniversity of Victoria, Computer Science, Faculty of Engineering, Canada, Laura NenziUniversity of Trieste, Bashar NuseibehThe Open University (UK) & Lero (Ireland), Liliana PasqualeUniversity College Dublin & Lero, Ireland, Wolfgang ReisigHumboldt-Universität zu Berlin, Germany, Heinz SchmidtRMIT Australia, Christos TsigkanosTechnische Universität Wien, Haiyan ZhaoPeking University