Model Based Approach for Context Aware and Adaptive User Interface Generation

User interface design and development for ubiquitous software applications is challenged by the presence of varying contexts. Context comprises of user’s computing platform, the environment in which the user is interacting with the application and user characteristics which comprise of user’s behavior during interaction and user preferences for interface display and interaction. We present a framework for adaptive user interface generation where adaptation occurs when context changes. This framework introduces three new concepts. First, formalization for representing context is introduced. Our design of context specification is unique since it reflects the association of context with level and nature of user interface adaptation. Secondly, user interface generation life cycle is studied and we define a context model on top of task model to introduce the contextual conditions into user interface generation process. Using the context model, user interface designer can specify contextual requirements and its effect on the user interface. Third, context aware adaptation of user interfaces is achieved by mapping context specifications to various levels of user interface generation life cycle. We designed a specification language called rule specification using which the user interface designer can specify the mapping. With the new design of context representation, context model, and rule specification, we demonstrate how changes in contexts adapts task model which in turn adapts the user interface. Reena G. Hanumansetty Acknowledgements and Dedications iii ACKNOWLEDGEMENTS I would like to express my gratitude to my thesis advisor, Dr. Denis Gracanin, for his valuable guidance, encouragement, and for taking time off his busy schedule to provide invaluable input towards completing my Master’s thesis. I would also like to thank him for the laboratory resources. I am grateful to Dr. Mohamed Eltoweissy who has also guided me and helped me improve my researching skills. I would also like to thank Dr. Shawn Bohner for his valuable input and guidance while working towards my thesis. I extend my gratitude to all the researchers involved in CTT, and USIXML mailing lists who shared their views and provided their insight into my views. I would like to acknowledge and thank Ph.D. students Xiaoyu Zhang, and Boby George for their input while working towards my thesis. I appreciate all support provided by faculty, staff and my colleagues in the Department of Computer Science, Virginia Tech in National Capital Region. I would also like to thank my parents and my brother’s family for all their support, encouragement, care, and good wishes to help me complete my thesis. Thank you God for everything. Thank you all for making me a better person.