A parallel tree based strategy for T-way combinatorial interaction testing

Abstract

All software systems are built with basic components which interact with each other through predefined combination rules. As the number of components increases, the interactions between the components also increases exponentially which cause the combinatorial explosion problem. This mean complete (exhaustive) testing becomes unreasonable due to the huge number of possible combinations. Although 2-way interaction testing (i.e. pairwise testing) can relief and detect 50-97 percent of errors, empirical evidence has proved that 2-way interaction testing is a poor strategy for testing highly interactive systems and it has been showed that most of the errors are triggered by the interaction of 2-6 input parameters. In this paper we enhanced our previous strategy, "A Tree Based Strategy for Test Data Generation and Cost Calculation" by applying parallel algorithms to go beyond pairwise testing. The proposed strategy can support higher interaction testing. The designed algorithms are described in details with efficient empirical results. © 2011 Springer-Verlag.