Computer networks and internets
Computer networks and internets
Managing mailing lists
Distributed Feature Composition: A Virtual Architecture for Telecommunications Services
IEEE Transactions on Software Engineering
Composing features and resolving interactions
SIGSOFT '00/FSE-8 Proceedings of the 8th ACM SIGSOFT international symposium on Foundations of software engineering: twenty-first century applications
Using SPIN for feature interaction analysis—a case study
SPIN '01 Proceedings of the 8th international SPIN workshop on Model checking of software
The Java Programming Language
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
Red Hat Linux Firewalls
SIP: Understanding the Session Initiation Protocol, Second Edition
SIP: Understanding the Session Initiation Protocol, Second Edition
Managing run-time interactions between call-processing features [intelligent networks]
IEEE Communications Magazine
Methods of addressing the interactions of intelligent network services with embedded switch services
IEEE Communications Magazine
Predicting feature interactions by using inconsistency models
Computer Networks: The International Journal of Computer and Telecommunications Networking
Email FI identification and resolution with model checking
Journal of Network and Computer Applications
Exploring feature interactions in the wild: the new feature-interaction challenge
Proceedings of the 5th International Workshop on Feature-Oriented Software Development
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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 behaviors, and this effect is known as feature interaction-FI. After a brief review of FI detection principles, we propose an interaction resolution adviser, consisting of two phases. The first phase implements an initial selection, by filtering the features that satisfy a set of formulas. We describe several strategies according to the nodes that participate in the FI resolution. The second phase selects the feature for execution, and adapts parameters, according to user policies. The interaction resolution adviser is distributed, scalable and independent of the applications and their features.