Deriving interaction-prone scenarios in feature interaction filtering with use case maps

Feature interactions (FIs) occur when features of different communication services interfere with each other FI filtering is a pre-processing step before the FI detection, which roughly identifies FI-prone service combinations based on simple indications of the FIs. We have previously (Proc. 6th Intl. Workshop on Feature Interactions in Telecom. Networks and Distributed Systems, pp. 163-178, 2000) proposed an FI filtering method at the requirements stage using use case maps (UCMs). This method identifies FI-prone service combinations by focusing on changes in the user's scenarios before/after the service composition, but it does not tell which of the scenarios in the compound services has the potential for FIs. In this paper, as an extension of the previous method, we propose a new method to derive FI-prone scenarios from the FI-prone combinations obtained by the previous method. From many practical FIs, we first make the following observations: (a) FI tends to occur in scenarios where both services are activated, and (b) FI tends to occur in scenarios where a service by-passes a feature of the other service. Then, based on these observations, we propose heuristics on the UCM scenario paths to derive FI-prone scenarios. An experimental evaluation demonstrates that the derived scenarios successfully cover all scenarios that lead to actual FIs.