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Reachability analysis of feature interactions: a progress report
ISSTA '96 Proceedings of the 1996 ACM SIGSOFT international symposium on Software testing and analysis
Feature interaction detection contest of the Fifth International Workshop on feature interactions
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue on the feature interactions in telecommunications systems
Using SPIN for feature interaction analysis—a case study
SPIN '01 Proceedings of the 8th international SPIN workshop on Model checking of software
Verifying cross-cutting features as open systems
Proceedings of the 10th ACM SIGSOFT symposium on Foundations of software engineering
Feature interaction: a critical review and considered forecast
Computer Networks: The International Journal of Computer and Telecommunications Networking
Feature Execution Trees and Interactions
PDPTA '02 Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications - Volume 3
A feature manager approach to the analysis of component-interactions
FMOODS '02 Proceedings of the IFIP TC6/WG6.1 Fifth International Conference on Formal Methods for Open Object-Based Distributed Systems V
Telecommunication service description using state transition rules
IWSSD '91 Proceedings of the 6th international workshop on Software specification and design
Distributed resolution of feature interactions for internet applications
Computer Networks: The International Journal of Computer and Telecommunications Networking
Email FI identification and resolution with model checking
Journal of Network and Computer Applications
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Internet applications, such as Email, VoIP and WWW, have been enhanced with many features. However, the introduction and modification of features may result in undesired behaviours, and this effect is known as feature interaction-FI. In this paper we propose a proactive approach for FI detection. Supported by sets of all possible events, predicates and inconsistent behaviours, we generate hypothetical new features that interact with a given feature. By predicting FIs, the feature subscriber may define, in advance, all mechanisms to resolve the FIs that may occur in the future. We adopt a semantic model, based on group theory, for the feature axiomatic specification. The algorithms that generate new features do not depend on the particular data structures used in the semantic model of the feature specification.