G2Way-A Backtracking Strategy for Pairwise Test Data Generation

Our continuous dependencies on software (i.e. to assist as well as facilitate our daily chores) often raise dependability issue particularly when software is being employed harsh and life threatening or (safety) critical applications. Here, rigorous software testing becomes immensely important. Many combinations of possible input parameters, hardware/software environments, and system conditions need to be tested and verified against for conformance. Due to resource constraints as well as time and costing factors, considering all exhaustive test possibilities would be impossible (i.e. due to combinatorial explosion problem). Earlier work suggests that pairivise sampling strategy (i.e. based on two-way parameter interaction) can be effective. Building and complementing earlier work, this paper discusses an efficient pairivise test data generation strategy, called G2Way. In doing so, this paper demonstrates the correctness of G2Way as well as compares its effectiveness against existing strategies including AETG and its variations, IPO, SA, GA, ACA, and All Pairs. Empirical evidences demonstrate that G2Way, in some cases, outperfonned other strategies in terms of the number of generated test data within reasonable execution time.