Properties of realistic feature models make combinatorial testing of product lines feasible

Abstract

Feature models and associated feature diagrams allow modeling and visualizing the constraints leading to the valid products of a product line. In terms of their expressiveness, feature diagrams are equivalent to propositional formulas which makes them theoretically expensive to process and analyze. For example, satisfying propositional formulas, which translates into finding a valid product for a given feature model, is an NP-hard problem, which has no fast, optimal solution. This theoretical complexity could prevent the use of powerful analysis techniques to assist in the development and testing of product lines. However, we have found that satisfying realistic feature models is quick. Thus, we show that combinatorial interaction testing of product lines is feasible in practice. Based on this, we investigate covering array generation time and results for realistic feature models and find where the algorithms can be improved. © 2011 Springer-Verlag.