Submission deadline: CLOSED
Publication: Nov./Dec. 2017
Software systems are becoming more context sensitive and increasingly exploit contextual information to handle the diversity of changes in and conditions of their environment. In specific application domains such as automotive systems, marine and aviation systems, windmill farms, and airport management systems, the timely use of and adaptation to contextual information is critical for the system’s normal operation. Consequently, a major concern is acquiring, analyzing, modeling, and managing contextual information for the plethora of systems that need to react and adapt to new contexts. These activities require appropriate software modeling and development techniques.
Moreover, the diverse scenarios that are driven by changes in the context demand software variability solutions that can dynamically select among alternatives. In particular, the ability to cope with different scenarios and options in which a system must select and adapt to new contexts at runtime introduces an extra level of complexity. This is because systems must make runtime decisions depending on varying context conditions. Emerging paradigms such as dynamic software product lines and runtime variability mechanisms play a central role to model and manage the variations using both context and noncontext features. Other emerging approaches are context-oriented programming languages that can handle the behavior of systems using contextual behavioral adaptations that can be activated or replaced dynamically to accommodate the systems’ and users’ varying needs.
This special issue will feature a variety of techniques, approaches, and case studies for modeling and developing context-sensitive systems that modify their behavior dynamically accordingly to varying conditions. We invite contributions related but not limited to
- context variability analysis and modeling techniques for context-aware systems;
- static and dynamic variability approaches dealing with context information;
- raising the awareness of software engineers, industry, and users for dealing with changes due to contextual variability;
- reconfiguration, rebinding, and dynamic-composition strategies for dealing with changing context information in self-adaptive and autonomous systems;
- dynamic adaptation and human interaction using context knowledge;
- context-variability-modeling challenges and solutions in application domains that rely on contextual information at runtime (for example, smart healthcare, intelligent vehicles, robotics and drones, Internet of Things systems, and smart cities), highlighting the strengths, weaknesses, and challenges of implementing such systems with context in mind;
- ontologies for discriminating and disambiguating related context information managing the behavior at runtime;
- collaborative aspects and feature dependencies for modeling software variability using context information in systems that exchange information in real time;
- context-oriented programming languages and other solutions for implementing context variability at runtime; and
- security aspects and solutions of dynamic adaptability in safety-critical scenarios.
Theme Issue Guest Editors
- Kim Mens, Université catholique de Louvain
- Rafael Capilla, Rey Juan Carlos University
- Thomas Kropf, Robert Bosch Car Multimedia and the University of Tübingen
- Herman Hartmann, NXP Semiconductors
Manuscripts must not exceed 3,000 words including figures and tables, which count for 250 words each. Submissions exceeding these limits might be rejected without refereeing. Articles deemed within the theme and scope will be peer reviewed and are subject to editing for magazine style, clarity, organization, and space. We reserve the right to edit the title of all submissions. Be sure to include the name of the theme issue for which you’re submitting.
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