A Methodology for Feature Interaction Detection in the AIN 0.1 Framework

  • Authors:
  • Fuchun Joseph Lin;Hong Liu;Abhrajit Ghosh

  • Affiliations:
  • Bellcore Applied Research, Morristown, NJ;Bellcore Applied Research, Morristown, NJ;Bellcore Applied Research, Morristown, NJ

  • Venue:
  • IEEE Transactions on Software Engineering
  • Year:
  • 1998

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, we propose an integrated methodology for specifying AIN and switch-based features and analyzing their interactions in the AIN 0.1 framework. The specification of each individual feature is tied to the AIN call model and requires only minimum amount of information in terms of control and data for interaction analysis. Once a feature is specified, its specification is then validated for consistency with respect to control and data. Interaction analysis is conducted for a set of features based on the sharing of call variables between the SSP and the SCP. With this approach, one can detect the following interactions involving AIN features: 1) side-effects, where a call variable modified by one feature is used by another feature and 2) disabling, where one feature disconnects a call, preventing another feature from execution. We also develop a theory that is based on the computation of sequences of messages exchanged between the SSP and the SCP and their call variable usage. This theory is shown to dramatically reduce the number of cases considered during the analysis. A brief overview of a tool that makes use of this methodology to aid in the task of feature interaction detection is also given.