Predicting feature interactions by using inconsistency models

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.