A framework for enhanced feature models based on mathematical analysis

A Feature Model is a tree like structure that represents the commonality and variability in Software Product Lines. During analysis required information is extracted from a feature model. In the literature a number of techniques have been presented for the analysis of feature models. Quality of a Feature Model is of prime significance because it is used for the development of families of software. The quality of feature models is affected by the presence of errors. There is a need for a mechanism that could enhance the quality of a feature model by removing all inconsistency, anomaly and redundancy based errors. I am proposing a mathematical technique for the analysis of Feature Models that will lead towards their quality enhancement.