Software product line (SPL) techniques handle the construction of customized systems. One of the most
common representations of the decisions a customer can make in SPLs is feature models (FMs). An FM
represents the relationships among common and variable features in an SPL. Features are a representation
of the characteristics in a system that are relevant to customers.
FMs are subject to change since the set of features and their relationships can change along an SPL lifecycle.
Due to this evolution, the consistency of FMs may be compromised. There exist some approaches to
detect and explain inconsistencies in FMs, however this process can take a long time for large FMs.
In this paper we present a complementary approach to dealing with inconsistencies in FM evolution
scenarios that improves the performance for existing approaches reducing the impact of change to the
smallest part of an FM that changes. To achieve our goal, we formalize FMs from an ontological perspective
and define constraints that must be satisfied in FMs to be consistent. We define a set of primitive
operations that modify FMs and which are responsible for the FM evolution, analyzing their impact on
the FM consistency. We propose a set of predefined strategies to keep the consistency for error-prone
operations.
As a proof-of-concept we present the results of our experiments, where we check for the effectiveness
and efficiency of our approach in FMs with thousands of features. Although our approach is limited by the
kinds of consistency constraints and the primitive operations we define, the experiments present a significant
improvement in performance results in those cases where they are applicable.Comisión Interministerial de Ciencia y Tecnología TIN2009-07366Junta de Andalucía TIC-5906Junta de Andalucía P07-TIC-253
