T - Way Strategies and Its Applications for Combinatorial Testing

The demand for multi-functional software has grown drastically over the years. To cater for this demand, software engineers are forced to develop complex software with increasing number of input parameters. As a result, more and more dependencies between input parameters are to be expected, opening more possibilities of faults due to interactions. Although traditional static and dynamic testing strategies (e.g. boundary value analysis, cause and effect analysis and equivalent partitioning) are useful in fault detection and prevention [1], however they are not sufficiently effective to detect faults due to interaction. As a result, many researchers nowadays are focusing on sampling strategy that is based on interaction testing (termed t-way testing strategies where t indicates the interaction strength) [2].