Generative programming: methods, tools, and applications
Generative programming: methods, tools, and applications
Location-aided routing (LAR) in mobile ad hoc networks
Wireless Networks
Model Checking Partial State Spaces with 3-Valued Temporal Logics
CAV '99 Proceedings of the 11th International Conference on Computer Aided Verification
Towards a Better Understanding of Context and Context-Awareness
HUC '99 Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing
Contextual patterns in mobile service usage
Personal and Ubiquitous Computing
Automated reasoning for multi-step feature model configuration problems
Proceedings of the 13th International Software Product Line Conference
Formal modelling of feature configuration workflows
Proceedings of the 13th International Software Product Line Conference
A survey of context modelling and reasoning techniques
Pervasive and Mobile Computing
FUSION: a framework for engineering self-tuning self-adaptive software systems
Proceedings of the eighteenth ACM SIGSOFT international symposium on Foundations of software engineering
Usage context as key driver for feature selection
SPLC'10 Proceedings of the 14th international conference on Software product lines: going beyond
Scalable routing strategies for ad hoc wireless networks
IEEE Journal on Selected Areas in Communications
Proceedings of the 16th International Software Product Line Conference - Volume 2
Runtime variability for dynamic reconfiguration in wireless sensor network product lines
Proceedings of the 16th International Software Product Line Conference - Volume 2
Staged configuration of dynamic software product lines with complex binding time constraints
Proceedings of the Eighth International Workshop on Variability Modelling of Software-Intensive Systems
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Dynamic Software Product Lines (DSPLs) provide a promising approach for planning and applying runtime reconfiguration scenarios to adaptive software systems. However, applying DSPLs in the vital domain of highly context-aware systems, e.g., mobile devices, is obstructed by the inherently limited resources being insufficient to handle large, constrained (re-)configurations spaces. To tackle these drawbacks, we propose a novel model-based approach for designing DSPLs in a way that allows for a trade-off between precomputation of reconfiguration scenarios at development time and on-demand evolution at runtime. Therefore, we (1) enrich feature models with context information to reason about potential context changes, and (2) specify context-aware reconfiguration processes on the basis of a scalable transition system incorporating state space abstractions and incremental refinement at runtime. We illustrate our concepts by means of a smartphone case study and present an implementation and evaluation considering different trade-off metrics.