Deriving Interaction-Prone Scenarios in Feature Interaction Filtering with Use Case Maps

Feature interactions (FIs, in short) occur when features of different communication services interfere with each other. The FI filtering is a pre-processing before the FI detection, which roughly identifies FI-prone service combinations based on simple indications of the FIs. We have previously proposed an FI filtering method at requirements stage using Use Case Maps (UCMs). This method identifies FI-prone service combinations by focusing on changes in user’s scenarios before/after the service composition, but does not tell which scenarios in the compound services have a potential of 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 two observations: (a) FI tends to occur in scenarios where both services are activated, and (b) FI tends to occur in scenarios where a service bypasses a feature of the other service. Then, based on the 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.